Earth Observing System Data Assimilation Research Articles

Comparison of scattering ratio profiles retrieved from ALADIN/Aeolus and CALIOP/CALIPSO observations and preliminary estimates of cloud fraction profiles

Abstract. The space-borne active sounders have been contributing invaluable vertically resolved information of atmospheric optical properties since the launch of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) in 2006. To build long-term records from space-borne lidars useful for climate studies, one has to understand the differences between successive space lidars operating at different wavelengths, flying on different orbits, and using different viewing geometries, receiving paths, and detectors. In this article, we compare the results of Atmospheric Laser Doppler INstrument (ALADIN) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidars for the period from 28 June to 31 December 2019. First, we build a dataset of ALADIN–CALIOP collocated profiles (Δdist<1∘; Δtime<6 h). Then we convert ALADIN's 355 nm particulate backscatter and extinction profiles into the scattering ratio vertical profiles SR(z) at 532 nm using molecular density profiles from Goddard Earth Observing System Data Assimilation System, version 5 (GEOS-5 DAS). And finally, we build the CALIOP and ALADIN globally gridded cloud fraction profiles CF(z) by applying the same cloud detection threshold to the SR(z) profiles of both lidars at the same spatial resolution. Before comparing the SR(z) and CF(z) profiles retrieved from the two analyzed lidar missions, we performed a numerical experiment to estimate the best achievable cloud detection agreement CDAnorm(z) considering the differences between the instruments. We define CDAnorm(z) in each latitude–altitude bin as the occurrence frequency of cloud layers detected by both lidars, divided by a cloud fraction value for the same latitude–altitude bin. We simulated the SR(z) and CF(z) profiles that would be observed by these two lidars if they were flying over the same atmosphere predicted by a global model. By analyzing these simulations, we show that the theoretical limit for CDAnormtheor(z) for a combination of ALADIN and CALIOP instruments is equal to 0.81±0.07 at all altitudes. In other words, 19 % of the clouds cannot be detected simultaneously by two instruments due to said differences. The analyses of the actual observed CALIOP–ALADIN collocated dataset containing ∼78 000 pairs of nighttime SR(z) profiles revealed the following points: (a) the values of SR(z) agree well up to ∼3 km height. (b) The CF(z) profiles show agreement below ∼3 km, where ∼80 % of the clouds detected by CALIOP are detected by ALADIN as expected from the numerical experiment. (c) Above this height, the CDAnormobs(z) reduces to ∼50 %. (d) On average, better sensitivity to lower clouds skews ALADIN's cloud peak height in pairs of ALADIN–CALIOP profiles by ∼0.5±0.6 km downwards, but this effect does not alter the heights of polar stratospheric clouds and high tropical clouds thanks to their strong backscatter signals. (e) The temporal evolution of the observed CDAnormobs(z) does not reveal any statistically significant change during the considered period. This indicates that the instrument-related issues in ALADIN L0/L1 have been mitigated, at least down to the uncertainties of the following CDAnormobs(z) values: 68±12 %, 55±14 %, 34±14 %, 39±13 %, and 42±14 % estimated at 0.75, 2.25, 6.75, 8.75, and 10.25 km, respectively.

Sensitivity of low‐tropospheric Arctic temperatures to assimilation of AIRS cloud‐cleared radiances: Impact on midlatitude waves

AbstractIn this work it is shown that the prediction of individual midlatitude waves in a global forecast framework may benefit from the assimilation of cloud‐cleared radiances (CCRs) from the Atmospheric Infrared Sounder (AIRS). The assimilation of CCRs, relative to clear‐sky radiances, provides more information in high‐latitude areas affected by broken low‐level stratus clouds, which are common over north polar latitudes during the summer and autumn seasons. This added information in cloudy regions produces slightly lower low‐level temperatures and lower mid‐tropospheric heights (through hydrostatic adjustment) over the Arctic and part of northeastern Siberia. In areas that are both dynamically unstable (with the potential for rapid error growth) and data void (as observed by clear‐sky radiances), the assimilation of CCRs provides valuable information that can improve the representation of individual baroclinic waves and their subsequent forecasts. The assimilation of AIRS CCRs slightly modifies the geopotential height gradients between the Arctic and the midlatitudes, leading to improvements in the forecast of individual baroclinic waves, as is shown through three case‐studies. The set of observing system experiments (OSEs) is performed with the NASA Goddard Earth Observing System (GEOS) data assimilation and forecast system during boreal autumn 2014. AIRS CCRs are thinned to approximately one quarter the density of operationally assimilated AIRS radiances, consistent with their higher information content. Global 6‐hourly analyses are produced from 01 September to 10 November 2014 and seven‐day forecasts are initialized at 0000 UTC daily. Since the CCR methodology is widely applicable, these findings are also relevant to other infrared sensors.

Toward a Reanalysis of Stratospheric Ozone for Trend Studies: Assimilation of the Aura Microwave Limb Sounder and Ozone Mapping and Profiler Suite Limb Profiler Data

AbstractCompatibility of the stratospheric ozone profile data from the Ozone Mapping and Profiler Suite Limb Profiler (OMPS‐LP) and the Microwave Limb Sounder (MLS) is assessed in the context of a continuity requirement for future reanalyses. A methodology for the assimilation of OMPS‐LP data into the Goddard Earth Observing System data assimilation system with a stratospheric chemistry module is developed. It is demonstrated that a simple homogenization technique significantly reduces the bias between OMPS‐LP and MLS analyses. With the homogenization applied, the mean difference between the two analyses is within 3% and the difference standard deviation within 10%, consistent with the estimated uncertainties of the satellite ozone data. Larger differences are seen in the tropical lower stratosphere. The MLS and OMPS‐LP assimilation experiments agree very well with independent data from ozonesondes and the Atmospheric Chemistry Experiment Fourier Transform Spectrometer. Heterogeneous ozone depletion during polar spring in both hemispheres as well as ozone transport during the 2016 quasi‐biennial oscillation disruption event are realistically represented in both analyses. This work establishes a step toward achieving continuity of the post‐2004 ozone record in future reanalyses, necessary for trend and long‐term ozone variability studies, although further development is needed to address a drift in the OMPS‐LP ozone data.

The ENSO and QBO Impact on Ozone Variability and Stratosphere‐Troposphere Exchange Relative to the Subtropical Jets

AbstractThe El Niño–Southern Oscillation (ENSO) and the Quasi‐Biennial Oscillation (QBO) are natural sources of ozone variability in the tropical and midlatitude upper troposphere and lower stratosphere. Regional tropospheric ozone variations have previously been attributed to ENSO‐ and QBO‐induced changes in stratosphere‐troposphere exchange around the subtropical jets (STJs). We use Goddard Earth Observing System Data Assimilation System analyses of Ozone Monitoring Instrument and Microwave Limb Sounder ozone data mapped to a STJ coordinate to examine the influence of ENSO and QBO on global and regional variability of upper troposphere and lower stratosphere ozone, and tropopause folding stratosphere‐troposphere exchange. These coordinates eliminate the apparent variability due to the changing location of the STJ, which is itself influenced by ENSO. The ENSO influence on ozone variability near the STJ and in tropopause folds is much greater than the QBO influence, although both are small in a hemispheric mean. On regional scales, the ozone sensitivity to ENSO associated with tropopause folding is strongly positive in some regions and strongly negative in others, which largely cancel in the hemispheric mean. Poleward of the STJs, the sensitivities of stratospheric ozone to ENSO and QBO are large and similar in magnitude but are opposite in phase. Thus, the ozone responses to ENSO and QBO can largely cancel or reinforce, depending on their relative phases. These results can be used to evaluate and compare modeled QBO and ENSO influences on ozone variability that removes the first‐order impact of differences in the location of the STJs.

Global Assimilation of Loon Stratospheric Balloon Observations

AbstractAccurate analyses of stratospheric winds are important for determining realistic constituent transport and providing improved diagnostic studies and forecasts of the stratosphere. This study examines impacts on global meteorological analyses resulting from using winds derived from Loon superpressure balloons in the lower stratosphere (hereafter Loon winds) as additional input observations to the Goddard Earth Observing System (GEOS) data assimilation system. To fully investigate the impacts of assimilating the Loon winds, two steps are taken: (1) comparison of the GEOS analysis winds with Loon winds (Control experiment) and (2) examination of the impacts of assimilating the Loon winds into the GEOS data assimilation system (Loon experiment). The time period selected is June–August 2014 when over 150 Loon balloons were launched, mainly in the Southern Hemisphere. In the middle latitudes, the Loon winds and Control winds agree well (Loon balloon zonal wind observation minus forecast, O − F, root‐mean‐square (RMS) values of ~2.75 m/s) and assimilating the Loon winds has a small impact (O − F RMS values unchanged). In the tropics, the Loon observations and Control analysis winds differ more than in middle latitudes (zonal wind O − F RMS ~3.75 m/s) and assimilating the Loon winds improves the zonal wind O − F RMS by ~1 m/s. In selected cases where the Loon observations and Control analysis differ greatly (O − F RMS values greater than 10 m/s), assimilating Loon winds significantly decreases the zonal wind O − F RMS by 5 m/s. These decreases in O − F RMS values show that the 6‐hr forecasts are improved at the Loon balloon observation locations.

Impact of adaptively thinned AIRS cloud-cleared radiances on tropical cyclone representation in a global data assimilation and forecast system.

A simple adaptive thinning methodology for Atmospheric Infrared Sounder (AIRS) radiances is evaluated through a combination of Observing System Experiments (OSEs) and adjoint methodologies. The OSEs are performed with the NASA Goddard Earth Observing System (GEOS, version 5) data assimilation and forecast model. In addition, the adjoint-based forecast sensitivity observation impact technique is applied to assess fractional contributions of sensors in different thinning configurations. The adaptive strategy uses a denser AIRS coverage in a moving domain centered around tropical cyclones (TCs), sparser everywhere else. The OSEs consist of two sets of data assimilation runs that cover the period from September 1st to 10 November 2014, with the first 20 days discarded for spin-up. Both sets assimilate all conventional and satellite observations used operationally. In addition, one ingests clear-sky AIRS radiances, the other cloud-cleared radiances, each comprising multiple thinning strategies. Daily 7-day forecasts are initialized from all these analyses and evaluated with focus on TCs over the Atlantic and the Pacific. Evidence is provided on the effectiveness of this simple TC-centered adaptive radiance thinning strategy, in full agreement with previous theoretical studies. Specifically, global skill increases, and tropical cyclone representation is substantially improved. The improvement is particularly strong when cloud-cleared radiances are assimilated. Finally, the article suggests that cloud-cleared radiances, if thinned more aggressively than the currently used clear-sky radiances, could successfully replace them with large improvements in TC forecasting and no loss of global skill.

Global O3-CO Correlations in a Chemistry and Transport Model During July-August: Evaluation with TES Satellite Observations and Sensitivity to Input Meteorological Data and Emissions.

We examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618hPa) O3-CO correlations determined by the measurements from Tropospheric Emission Spectrometer (TES) aboard NASA's Aura satellite during boreal summer (July-August). The model is driven by three meteorological data sets (fvGCM with sea surface temperature for 1995, GEOS4-DAS for 2005, and MERRA for 2005), allowing us to examine the sensitivity of model O3-CO correlations to input meteorological data. Model simulations of radionuclide tracers (222Rn, 210Pb, and 7Be) are used to illustrate the differences in transport-related processes among the meteorological data sets. Simulated O3 values are evaluated with climatological ozone profiles from ozonesonde measurements and satellite tropospheric O3 columns. Despite the fact that three simulations show significantly different global and regional distributions of O3 and CO concentrations, all simulations show similar patterns of O3-CO correlations on a global scale. These patterns are consistent with those derived from TES observations, except in the tropical easterly biomass burning outflow regions. Discrepancies in regional O3-CO correlation patterns in the three simulations may be attributed to differences in convective transport, stratospheric influence, and subsidence, among other processes. To understand how various emissions drive global O3-CO correlation patterns, we examine the sensitivity of GMI/MERRA model-calculated O3 and CO concentrations and their correlations to emission types (fossil fuel, biomass burning, biogenic, and lightning NOx emissions). Fossil fuel and biomass burning emissions are mainly responsible for the strong positive O3-CO correlations over continental outflow regions in both hemispheres. Biogenic emissions have a relatively smaller impact on O3-CO correlations than other emissions, but are largely responsible for the negative correlations over the tropical eastern Pacific, reflecting the fact that O3 is consumed and CO generated during the atmospheric oxidation process of isoprene under low NOx conditions. We find that lightning NOx emissions degrade both positive correlations at mid-/high- latitudes and negative correlations in the tropics because ozone production downwind of lightning NOx emissions is not directly related to the emission and transport of CO. Our study concludes that O3-CO correlations may be used effectively to constrain the sources of regional tropospheric O3 in global 3-D models, especially for those regions where convective transport of pollution plays an important role.

The 2015/2016 El Niño Event in Context of the MERRA-2 Reanalysis: A Comparison of the Tropical Pacific with 1982/1983 and 1997/1998.

The 2015/2016 El Niño is analyzed using atmospheric/oceanic analysis produced using the Goddard Earth Observing System (GEOS) data assimilation systems. As well as describing the structure of the event, a theme of the work is to compare and contrast it with two other strong El Niños, in 1982/1983 and 1997/1998. These three El Niño events are included in the Modern-Era Retrospective analysis for Research and Applications (MERRA) and in the more recent MERRA-2 reanalyses. MERRA-2 allows a comparison of fields derived from the underlying GEOS model, facilitating a more detailed comparison of physical forcing mechanisms in the El Niño events. Various atmospheric/oceanic structures indicate that the 2015/2016 El Niño maximized in the Niño3.4 region, with the large region of warming over most of the Pacific and Indian Ocean. The eastern tropical Indian Ocean, Maritime Continent, and western tropical Pacific are found to be less dry in boreal winter, compared to the earlier two strong events. While the 2015/2016 El Niño had an earlier occurrence of the equatorial Pacific warming and was the strongest event on record in the central Pacific, the 1997/1998 event exhibited a more rapid growth due to stronger westerly wind bursts and Madden-Julian Oscillation during spring, making it the strongest El Niño in the eastern Pacific. Compared to 1982/1983 and 1997/1998, the 2015/2016 event has a shallower thermocline over the eastern Pacific with a weaker zonal contrast of sub-surface water temperatures along the equatorial Pacific. While the three major ENSO events have similarities, each are unique when looking at the atmosphere and ocean surface and sub-surface.

A Linearized Prognostic Cloud Scheme in NASA’s Goddard Earth Observing System Data Assimilation Tools

Abstract A linearized prognostic cloud scheme has been developed to accompany the linearized convection scheme recently implemented in NASA’s Goddard Earth Observing System data assimilation tools. The linearization, developed from the nonlinear cloud scheme, treats cloud variables prognostically so they are subject to linearized advection, diffusion, generation, and evaporation. Four linearized cloud variables are modeled, the ice and water phases of clouds generated by large-scale condensation and, separately, by detraining convection. For each species the scheme models their sources, sublimation, evaporation, and autoconversion. Large-scale, anvil and convective species of precipitation are modeled and evaporated. The cloud scheme exhibits linearity and realistic perturbation growth, except around the generation of clouds through large-scale condensation. Discontinuities and steep gradients are widely used here and severe problems occur in the calculation of cloud fraction. For data assimilation applications this poor behavior is controlled by replacing this part of the scheme with a perturbation model. For observation impacts, where efficiency is less of a concern, a filtering is developed that examines the Jacobian. The replacement scheme is only invoked if Jacobian elements or eigenvalues violate a series of tuned constants. The linearized prognostic cloud scheme is tested by comparing the linear and nonlinear perturbation trajectories for 6-, 12-, and 24-h forecast times. The tangent linear model performs well and perturbations of clouds are well captured for the lead times of interest.

Next-generation angular distribution models for top-of-atmosphere radiative flux calculation from CERES instruments: methodology

Abstract. The top-of-atmosphere (TOA) radiative fluxes are critical components to advancing our understanding of the Earth's radiative energy balance, radiative effects of clouds and aerosols, and climate feedback. The Clouds and the Earth's Radiant Energy System (CERES) instruments provide broadband shortwave and longwave radiance measurements. These radiances are converted to fluxes by using scene-type-dependent angular distribution models (ADMs). This paper describes the next-generation ADMs that are developed for Terra and Aqua using all available CERES rotating azimuth plane radiance measurements. Coincident cloud and aerosol retrievals, and radiance measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from Goddard Earth Observing System (GEOS) data assimilation version 5.4.1 are used to define scene type. CERES radiance measurements are stratified by scene type and by other parameters that are important for determining the anisotropy of the given scene type. Anisotropic factors are then defined either for discrete intervals of relevant parameters or as a continuous functions of combined parameters, depending on the scene type. Significant differences between the ADMs described in this paper and the existing ADMs are over clear-sky scene types and polar scene types. Over clear ocean, we developed a set of shortwave (SW) ADMs that explicitly account for aerosols. Over clear land, the SW ADMs are developed for every 1° latitude × 1° longitude region for every calendar month using a kernel-based bidirectional reflectance model. Over clear Antarctic scenes, SW ADMs are developed by accounting the effects of sastrugi on anisotropy. Over sea ice, a sea-ice brightness index is used to classify the scene type. Under cloudy conditions over all surface types, the longwave (LW) and window (WN) ADMs are developed by combining surface and cloud-top temperature, surface and cloud emissivity, cloud fraction, and precipitable water. Compared to the existing ADMs, the new ADMs change the monthly mean instantaneous fluxes by up to 5 W m−2 on a regional scale of 1° latitude × 1° longitude, but the flux changes are less than 0.5 W m−2 on a global scale.

Inclusion of Linearized Moist Physics in NASA’s Goddard Earth Observing System Data Assimilation Tools

Abstract Inclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa–Schubert (RAS) convection scheme has been developed and tested in NASA’s Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encountered. Efficient filtering of these profiles is achieved by diagnosis of steep gradients in a reduced version of the operator of the tangent linear model. With filtering turned on, the inclusion of linearized moist physics increases the correlation between the nonlinear perturbation trajectory and the linear approximation of the perturbation trajectory. A month-long observation impact experiment is performed and the effect of including moist physics on the impacts is discussed. Impacts from moist-sensitive instruments and channels are increased. The effect of including moist physics is examined for adjoint sensitivity studies. A case study examining an intensifying Northern Hemisphere Atlantic storm is presented. The results show a significant sensitivity with respect to moisture.

Spatial and Annual Variation of Offshore Wind Resource in China

According to the Chinese Twelfth Five-Year Plan, two large scale wind farms are planned to be built in the shore of Shandong province and Guangdong province to meet the increasing electricity demand with economic development. Before the construction of wind farm, it is necessary to evaluate the wind potential and its temporal variation along the coast of Shandong province, Guangdong province and Zhejiang province that have been studied in this paper. The data used were obtained from Goddard Earth Observing System (GEOS) Data Assimilation System. The results showed that there is rich wind supply in Zhejiang province with small annual variation. Further away from shore, the wind energy will increase fastest in Guangdong area. The yield of wind energy in Shandong province is not as rich as in the other two provinces as predicted in the study. Furthermore, the layout of wind turbines in wind farm was also investigated to absorb wind energy at the highest efficiency by wind farm. Our results provide a reference for the future construction of wind farms.

A-train CALIOP and MLS observations of early winter Antarctic polar stratospheric clouds and nitric acid in 2008

Abstract. A-train Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Microwave Limb Sounder (MLS) observations are used to investigate the development of polar stratospheric clouds (PSCs) and the gas-phase nitric acid distribution in the early 2008 Antarctic winter. Observational evidence of gravity-wave activity is provided by Atmospheric Infrared Sounder (AIRS) radiances and infrared spectroscopic detection of nitric acid trihydrate (NAT) in PSCs is obtained from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Goddard Earth Observing System Data Assimilation System (GEOS-5 DAS) analyses are used to derive Lagrangian trajectories and to determine temperature-time histories of air parcels. We use CALIOP backscatter and depolarization measurements to classify PSCs and the MLS measurements to determine the corresponding gas-phase HNO3 as a function of temperature. For liquid PSCs the uptake of HNO3 follows the theoretical equilibrium curve for supercooled ternary solutions (STS), but at temperatures about 1 K lower as determined from GEOS-5. In the presence of solid phase PSCs, above the ice frost-point, the HNO3 depletion occurs over a wider range of temperatures (+2 to −7 K) distributed about the NAT equilibrium curve. Rapid gas-phase HNO3 depletion is first seen by MLS from from 23–25 May 2008, consisting of a decrease in the volume mixing ratio from 14 ppbv (parts per billion by volume) to 7 ppbv on the 46–32 hPa (hectopascal) pressure levels and accompanied by a 2–3 ppbv increase by renitrification at the 68 hPa pressure level. The observed region of depleted HNO3 is substantially smaller than the region bounded by the NAT existence temperature threshold. Temperature-time histories of air parcels demonstrate that the depletion is more clearly correlated with prior exposure to temperatures a few kelvin above the frost-point. From the combined data we infer the presence of large-size NAT particles with effective radii >5–7 μm and low NAT number densities <1 × 10−3 cm−3. This denitrification event is observed close to the pole in the Antarctic vortex before synoptic temperatures first fall below the ice frost point and before the widespread occurrence of large-scale NAT PSCs. An episode of mountain wave activity detected by AIRS on 28 May 2008 led to wave-ice formation in the rapid cooling phases over the Antarctic Peninsula and Ellsworth Mountains, seeding an outbreak of NAT PSCs that were detected by CALIOP and MIPAS. The NAT clouds formed at altitudes of 18–26 km in a polar freezing belt and appear to be composed of relatively small particles with estimated effective radii of around 1 μm and high NAT number densities >0.2 cm−3. This NAT outbreak is similar to an event previously reported from MIPAS observations in mid-June 2003.

Sensitivity of photolysis frequencies and key tropospheric oxidants in a global model to cloud vertical distributions and optical properties

Clouds directly affect tropospheric photochemistry through modification of solar radiation that determines photolysis frequencies. As a follow‐up study to our recent assessment of these direct radiative effects of clouds on tropospheric chemistry, this paper presents an analysis of the sensitivity of such effects to cloud vertical distributions and optical properties (cloud optical depths (CODs) and cloud single scattering albedo), in a global three‐dimensional (3‐D) chemical transport model. The model was driven with a series of meteorological archives (GEOS‐1 in support of the Stratospheric Tracers of Atmospheric Transport mission, or GEOS1‐STRAT, GEOS‐3, and GEOS‐4) generated by the NASA Goddard Earth Observing System (GEOS) data assimilation system. Clouds in GEOS1‐STRAT and GEOS‐3 have more similar vertical distributions (with substantially smaller CODs in GEOS1‐STRAT) while those in GEOS‐4 are optically much thinner in the tropical upper troposphere. We find that the radiative impact of clouds on global photolysis frequencies and hydroxyl radical (OH) is more sensitive to the vertical distribution of clouds than to the magnitude of column CODs. With random vertical overlap for clouds, the model calculated changes in global mean OH (J(O1D), J(NO2)) due to the radiative effects of clouds in June are about 0.0% (0.4%, 0.9%), 0.8% (1.7%, 3.1%), and 7.3% (4.1%, 6.0%) for GEOS1‐STRAT, GEOS‐3, and GEOS‐4, respectively; the geographic distributions of these quantities show much larger changes, with maximum decrease in OH concentrations of ∼15–35% near the midlatitude surface. The much larger global impact of clouds in GEOS‐4 reflects the fact that more solar radiation is able to penetrate through the optically thin upper tropospheric clouds, increasing backscattering from low‐level clouds. Model simulations with each of the three cloud distributions all show that the change in the global burden of ozone due to clouds is less than 5%. Model perturbation experiments with GEOS‐3, where the magnitude of 3‐D CODs are progressively varied from −100% to 100%, predict only modest changes (<5%) in global mean OH concentrations. J(O1D), J(NO2), and OH concentrations show the strongest sensitivity for small CODs and become insensitive at large CODs owing to saturation effects. Caution should be exercised not to use in photochemical models a value for cloud single scattering albedo lower than about 0.999 in order to be consistent with the current knowledge of cloud absorption at the ultraviolet wavelengths.

Comparison between Local Ensemble Transform Kalman Filter and PSAS in the NASA finite volume GCM – perfect model experiments

Abstract. This paper compares the performance of the Local Ensemble Transform Kalman Filter (LETKF) with the Physical-Space Statistical Analysis System (PSAS) under a perfect model scenario. PSAS is a 3D-Var assimilation system used operationally in the Goddard Earth Observing System Data Assimilation System (GEOS-4 DAS). The comparison is carried out using simulated winds and geopotential height observations and the finite volume Global Circulation Model with 72 grid points zonally, 46 grid points meridionally and 55 vertical levels. With forty ensemble members, the LETKF obtains analyses and forecasts with significantly lower RMS errors than those from PSAS, especially over the Southern Hemisphere and oceans. This observed advantage of the LETKF over PSAS is due to the ability of the 40-member ensemble LETKF to capture flow-dependent errors and thus create a good estimate of the evolving background uncertainty. An initial decrease of the forecast errors in the Northern Hemisphere observed in the PSAS but not in the LETKF suggests that the LETKF analysis is more balanced.

Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses

Abstract Global microwave rainfall retrievals from a five-satellite constellation, including the Tropical Rainfall Measuring Mission Microwave Imager, Special Sensor Microwave Imager from the Defense Meteorological Satellite Program F13, F14, and F15, and the Advanced Microwave Scanning Radiometer from the Earth Observing System Aqua, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System using a 1D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses is examined at various temporal and spatial scales. This study demonstrates that the 1D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly mean and 6-h time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1D VCA algorithm, by compensating for errors in the model’s moist time tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall–assimilation run especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicate that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity, are more realistically captured across the front.

Radiative effect of clouds on tropospheric chemistry in a global three‐dimensional chemical transport model

Clouds exert an important influence on tropospheric photochemistry through modification of solar radiation that determines photolysis frequencies (J‐values). We assess the radiative effect of clouds on photolysis frequencies and key oxidants in the troposphere with a global three‐dimensional (3‐D) chemical transport model (GEOS‐CHEM) driven by assimilated meteorological observations from the Goddard Earth Observing System data assimilation system (GEOS DAS) at the NASA Global Modeling and Assimilation Office (GMAO). We focus on the year of 2001 with the GEOS‐3 meteorological observations. Photolysis frequencies are calculated using the Fast‐J radiative transfer algorithm. The GEOS‐3 global cloud optical depth and cloud fraction are evaluated and generally consistent with the satellite retrieval products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Satellite Cloud Climatology Project (ISCCP). Results using the linear assumption, which assumes linear scaling of cloud optical depth with cloud fraction in a grid box, show global mean OH concentrations generally increase by less than 6% because of the radiative effect of clouds. The OH distribution shows much larger changes (with maximum decrease of ∼20% near the surface), reflecting the opposite effects of enhanced (weakened) photochemistry above (below) clouds. The global mean photolysis frequencies for J[O1D] and J[NO2] in the troposphere change by less than 5% because of clouds; global mean O3 concentrations in the troposphere increase by less than 5%. This study shows tropical upper tropospheric O3 to be less sensitive to the radiative effect of clouds than previously reported (∼5% versus ∼20–30%). These results emphasize that the dominant effect of clouds is to influence the vertical redistribution of the intensity of photochemical activity while global average effects remain modest, again contrasting with previous studies. Differing vertical distributions of clouds may explain part, but not the majority, of these discrepancies between models. Using an approximate random overlap or a maximum‐random overlap scheme to take account of the effect of cloud overlap in the vertical reduces the impact of clouds on photochemistry but does not significantly change our results with respect to the modest global average effect.

Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth’s Radiant Energy System Instrument on the Terra Satellite. Part I: Methodology

Abstract The Clouds and Earth’s Radiant Energy System (CERES) provides coincident global cloud and aerosol properties together with reflected solar, emitted terrestrial longwave, and infrared window radiative fluxes. These data are needed to improve the understanding and modeling of the interaction between clouds, aerosols, and radiation at the top of the atmosphere, surface, and within the atmosphere. This paper describes the approach used to estimate top-of-atmosphere (TOA) radiative fluxes from instantaneous CERES radiance measurements on the Terra satellite. A key component involves the development of empirical angular distribution models (ADMs) that account for the angular dependence of the earth’s radiation field at the TOA. The CERES Terra ADMs are developed using 24 months of CERES radiances, coincident cloud and aerosol retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from the Global Modeling and Assimilation Office (GMAO)’s Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) V4.0.3 product. Scene information for the ADMs is from MODIS retrievals and GEOS DAS V4.0.3 properties over the ocean, land, desert, and snow for both clear and cloudy conditions. Because the CERES Terra ADMs are global, and far more CERES data are available on Terra than were available from CERES on the Tropical Rainfall Measuring Mission (TRMM), the methodology used to define CERES Terra ADMs is different in many respects from that used to develop CERES TRMM ADMs, particularly over snow/sea ice, under cloudy conditions, and for clear scenes over land and desert.

The Computational Complexity and Parallel Scalability of Atmospheric Data Assimilation Algorithms

Abstract This paper quantifies the computational complexity and parallel scalability of two algorithms for four-dimensional data assimilation (4DDA) at NASA's Global Modeling and Assimilation Office (GMAO). The first, the Goddard Earth Observing System Data Assimilation System (GEOS DAS), uses an atmospheric general circulation model (GCM) and an observation-space-based analysis system, the Physical-Space Statistical Analysis System (PSAS). GEOS DAS is very similar to global meteorological weather forecasting data assimilation systems but is used at NASA for climate research. The second, the Kalman filter, uses a more consistent algorithm to determine the forecast error covariance matrix than does GEOS DAS. For atmospheric assimilation, the gridded dynamical fields typically have more than 106 variables; therefore, the full error covariance matrix may be in excess of a teraword. For the Kalman filter this problem will require petaflop s−1 computing to achieve effective throughput for scientific research.

The GEOS-3 Retrospective Data Assimilation System: The 6-Hour Lag Case

The fixed-lag Kalman smoother (FLKS) has been proposed as a framework to construct data assimilation procedures capable of producing high-quality climate research datasets. FLKS-based systems, referred to as retrospective data assimilation systems, are an extension to three-dimensional filtering procedures with the added capability of incorporating observations not only in the past and present time of the estimate, but also at future times. A variety of simplifications are necessary to render retrospective assimilation procedures practical. In this article, an FLKS-based retrospective data assimilation system implementation for the Goddard Earth Observing System Data Assimilation System is presented. The practicality of this implementation comes from the practicality of its underlying (filter) analysis system, that is, the physical-space statistical analysis system (PSAS). The behavior of two schemes is studied here. The first retrospective analysis (RA) scheme is designed simply to update the regular PSAS analyses with observations available at times ahead of the regular analysis times. Results are presented for when observations 6-h ahead of the analysis time are used to update the PSAS analyses and thereby to calculate the so-called lag-1 retrospective analyses. Consistency tests for this RA scheme show that the lag-1 retrospective analyses indeed have better 6-h predictive skill than the predictions from the regular analyses. This motivates the introduction of the second retrospective analysis scheme, which, at each analysis time, uses the 6-h retrospective analysis to create a new forecast to replace the forecast normally used in the PSAS analysis, and therefore allows the calculation of a revised (filter) PSAS analysis. This procedure is referred to as the retrospective-based iterated analysis (RIA) scheme. Results from the RIA scheme indicate its potential for improving the overall quality of the assimilation.