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R. Meneghini, J. A. Jones, T. Iguchi, K. Okamoto, and J. Kwiatkowski

Abstract

Satellite weather radars that operate at attenuating wavelengths require an estimate of path attenuation to reconstruct the range profile of rainfall. One such method is the surface reference technique (SRT), by which attenuation is estimated as the difference between the surface cross section outside the rain and the apparent surface cross section measured in rain. This and the Hitschfeld–Bordan method are used operationally to estimate rain rate using data from the precipitation radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. To overcome some of the problems associated with the latest operational version of the SRT, a hybrid surface reference is defined that uses information from the along-track and cross-track variations of the surface cross sections in rain-free areas. Over ocean, this approach eliminates most of the discontinuities in the path-attenuation field. Self-consistency of the estimates is tested by processing the orbits backward as well as forward. Calculations from 2 weeks of PR data show that 90% of the rain events over ocean for which the SRT is classified as reliable or marginally reliable are such that the absolute difference between the forward and backward estimates is less than 1 dB.

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Julian F. Quinting, Michael M. Bell, Patrick A. Harr, and Sarah C. Jones

Abstract

The structure and the environment of Typhoon Sinlaku (2008) were investigated during its life cycle in The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC). On 20 September 2008, during the transformation stage of Sinlaku’s extratropical transition (ET), research aircraft equipped with dual-Doppler radar and dropsondes documented the structure of the convection surrounding Sinlaku and low-level frontogenetical processes. The observational data obtained were assimilated with the recently developed Spline Analysis at Mesoscale Utilizing Radar and Aircraft Instrumentation (SAMURAI) software tool. The resulting analysis provides detailed insight into the ET system and allows specific features of the system to be identified, including deep convection, a stratiform precipitation region, warm- and cold-frontal structures, and a dry intrusion. The analysis offers valuable information about the interaction of the features identified within the transitioning tropical cyclone. The existence of dry midlatitude air above warm-moist tropical air led to strong potential instability. Quasigeostrophic diagnostics suggest that forced ascent during warm frontogenesis triggered the deep convective development in this potentially unstable environment. The deep convection itself produced a positive potential vorticity anomaly at midlevels that modified the environmental flow. A comparison of the operational ECMWF analysis and the observation-based SAMURAI analysis exhibits important differences. In particular, the ECMWF analysis does not capture the deep convection adequately. The nonexistence of the deep convection has considerable implications on the potential vorticity structure of the remnants of the typhoon at midlevels. An inaccurate representation of the thermodynamic structure of the dry intrusion has considerable implications on the frontogenesis and the quasigeostrophic forcing.

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Chris D. Jones, Matthew Collins, Peter M. Cox, and Steven A. Spall

Abstract

There is significant interannual variability in the atmospheric concentration of carbon dioxide (CO2) even when the effect of anthropogenic sources has been accounted for. This variability is well correlated with the El Niño–Southern Oscillation (ENSO) cycle. This behavior of the natural carbon cycle provides a valuable mechanism for validating carbon cycle models. The model in turn is a valuable tool for examining the processes involved in the relationship between ENSO and the carbon cycle.

A GCM coupled climate–carbon cycle model is used to study the mechanisms involved. The model simulates the observed temperature, precipitation, and CO2 response of the climate to the ENSO cycle. Climatic changes over land during El Niño events lead to decreased gross primary productivity and increased plant and soil respiration, and hence the terrestrial biosphere becomes a source of CO2 to the atmosphere. Conversely, during El Niño events, the ocean becomes a sink of CO2 because of reduction of equatorial Pacific outgassing as a result of decreased upwelling of carbon-rich deep water. During La Niña events the opposite occurs; the land becomes a sink and the ocean a source of CO2.

The magnitude of the model's response is such that the terrestrial biosphere releases about 1.8 GtC yr−1 for an El Niño with a Niño-3 index of magnitude 1 °C, and the oceans take up about 0.5 GtC yr−1. (1 GtC = 1015 g of carbon). The net global response is thus an increase in atmospheric CO2 of about 0.6 ppmv yr−1. This is in close agreement with the sensitivity of the observed CO2 record to ENSO events.

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A. M. Rogerson, P. D. Miller, L. J. Pratt, and C. K. R. T. Jones

Abstract

Kinematic models predict that a coherent structure, such as a jet or an eddy, in an unsteady flow can exchange fluid with its surroundings. The authors consider the significance of this effect for a fully nonlinear, dynamically consistent, barotropic model of a meandering jet. The calculated volume transport associated with this fluid exchange is comparable to that of fluid crossing the Gulf Stream through the detachment of rings. Although the model is barotropic and idealized in other ways, the transport calculations suggest that this exchange mechanism may be important in lateral transport or potential vorticity budget analyses for the Gulf Stream and other oceanic jets. The numerically simulated meandering jet is obtained by allowing a small-amplitude unstable meander to grow until a saturated state occurs. The resulting flow is characterized by finite-amplitude meanders propagating with nearly constant speed, and the results clearly illustrate the stretching and stirring of fluid particles along the edges of the recirculation regions south of the meander crests and north of the troughs. The fluid exchange and resulting transport across boundaries separating regions of predominantly prograde, retrograde, and recirculating motion is quantified using a dynamical systems analysis. The geometrical structures that result from the analysis are shown to be closely correlated with regions of the flow that are susceptible to high potential vorticity dissipation. Moreover, in a related study this analysis has been used to effectively predict the entrainment and detrainment of particles to and from the jet.

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Yonghong Yi, John S. Kimball, Lucas A. Jones, Rolf H. Reichle, and Kyle C. McDonald

Abstract

The authors evaluated several land surface variables from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) product that are important for global ecological and hydrological studies, including daily maximum (T max) and minimum (T min) surface air temperatures, atmosphere vapor pressure deficit (VPD), incident solar radiation (SWrad), and surface soil moisture. The MERRA results were evaluated against in situ measurements, similar global products derived from satellite microwave [the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E)] remote sensing and earlier generation atmospheric analysis [Goddard Earth Observing System version 4 (GEOS-4)] products. Relative to GEOS-4, MERRA is generally warmer (~0.5°C for T min and T max) and drier (~50 Pa for VPD) for low- and middle-latitude regions (<50°N) associated with reduced cloudiness and increased SWrad. MERRA and AMSR-E temperatures show relatively large differences (>3°C) in mountainous areas, tropical forest, and desert regions. Surface soil moisture estimates from MERRA (0–2-cm depth) and two AMSR-E products (~0–1-cm depth) are moderately correlated (R ~ 0.4) for middle-latitude regions with low to moderate vegetation biomass. The MERRA derived surface soil moisture also corresponds favorably with in situ observations (R = 0.53 ± 0.01, p < 0.001) in the midlatitudes, where its accuracy is directly proportional to the quality of MERRA precipitation. In the high latitudes, MERRA shows inconsistent soil moisture seasonal dynamics relative to in situ observations. The study’s results suggest that satellite microwave remote sensing may contribute to improved reanalysis accuracy where surface meteorological observations are sparse and in cold land regions subject to seasonal freeze–thaw transitions. The upcoming NASA Soil Moisture Active Passive (SMAP) mission is expected to improve MERRA-type reanalysis accuracy by providing accurate global mapping of freeze–thaw state and surface soil moisture with 2–3-day temporal fidelity and enhanced (≤9 km) spatial resolution.

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M. Toner, A. D. Kirwan Jr., B. L. Lipphardt, A. C. Poje, C. K. R. T. Jones, and C. E. Grosch

Abstract

A single-layer, reduced-gravity, double-gyre primitive equation model in a 2000 km × 2000 km square domain is used to test the accuracy and sensitivity of time-dependent Eulerian velocity fields reconstructed from numerically generated drifter trajectories and climatology. The goal is to determine how much Lagrangian data is needed to capture the Eulerian velocity field within a specified accuracy. The Eulerian fields are found by projecting, on an analytic set of divergence-free basis functions, drifter data launched in the active western half of the basin supplemented by climatology in the eastern domain. The time-dependent coefficients are evaluated by least squares minimization and the reconstructed fields are compared to the original model output. The authors find that the accuracy of the reconstructed fields depends critically on the spatial coverage of the drifter observations. With good spatial coverage, the technique allows accurate Eulerian reconstructions with under 200 drifters deployed in the 1000 km × 1400 km energetic western region. The base reconstruction error, achieved with full observation of the velocity field, ranges from 5% (with 191 basis functions) to 30% (with 65 basis functions). Specific analysis of the relation between spatial coverage and reconstruction error is presented using 180 drifters deployed in 100 different initial configurations that maximize coverage extremes. The simulated drifter data is projected on 107 basis functions for a 50-day period. The base reconstruction error of 15% is achieved when drifters occupy approximately 110 (out of 285) 70-km cells in the western region. Reconstructions from simulated mooring data located at the initial positions of representative good and poor coverage drifter deployments show the effect drifter dispersion has on data voids. The authors conclude that with appropriate coverage, drifter data could provide accurate basin-scale reconstruction of Eulerian velocity fields.

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Peter A. Stott, Gareth S. Jones, Jason A. Lowe, Peter Thorne, Chris Durman, Timothy C. Johns, and Jean-Claude Thelen

Abstract

The ability of climate models to simulate large-scale temperature changes during the twentieth century when they include both anthropogenic and natural forcings and their inability to account for warming over the last 50 yr when they exclude increasing greenhouse gas concentrations has been used as evidence for an anthropogenic influence on global warming. One criticism of the models used in many of these studies is that they exclude some forcings of potential importance, notably from fossil fuel black carbon, biomass smoke, and land use changes. Herein transient simulations with a new model, the Hadley Centre Global Environmental Model version 1 (HadGEM1), are described, which include these forcings in addition to other anthropogenic and natural forcings, and a fully interactive treatment of atmospheric sulfur and its effects on clouds. These new simulations support previous work by showing that there was a significant anthropogenic influence on near-surface temperature change over the last century. They demonstrate that black carbon and land use changes are relatively unimportant for explaining global mean near-surface temperature changes.

The pattern of warming in the troposphere and cooling in the stratosphere that has been observed in radiosonde data since 1958 can only be reproduced when the model includes anthropogenic forcings. However, there are some discrepancies between the model simulations and radiosonde data, which are largest where observational uncertainty is greatest in the Tropics and high latitudes.

Predictions of future warming have also been made using the new model. Twenty-first-century warming rates, following policy-relevant emissions scenarios, are slightly greater in HadGEM1 than in the Third Hadley Centre Coupled Ocean–Atmosphere General Circulation Model (HadCM3) as a result of the extra forcing in HadGEM1. An experiment in which greenhouse gases and other anthropogenic forcings are stabilized at 2100 levels and held constant until 2200 predicts a committed twenty-second-century warming of less than 1 K, whose spatial distribution resembles that of warming during the twenty-first century, implying that the local feedbacks that determine the pattern of warming do not change significantly.

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A. Philipp, P. M. Della-Marta, J. Jacobeit, D. R. Fereday, P. D. Jones, A. Moberg, and H. Wanner

Abstract

Reconstructed daily mean sea level pressure patterns of the North Atlantic–European region are classified for the period 1850 to 2003 to explore long-term changes of the atmospheric circulation and its impact on long-term temperature variability in the central European region. Commonly used k-means clustering algorithms resulted in classifications of low quality because of methodological deficiencies leading to local optima by chance for complex datasets. In contrast, a newly implemented clustering scheme combining the concepts of simulated annealing and diversified randomization (SANDRA) is able to reduce substantially the influence of chance in the cluster assignment, leading to partitions that are noticeably nearer to the global optimum and more stable. The differences between conventional cluster analysis and the SANDRA scheme are significant for subsequent analyses of single clusters—in particular, for trend analysis. Conventional indices used to determine the appropriate number of clusters failed to provide clear guidance, indicating that no distinct separation between clusters of circulation types exists in the dataset. Therefore, the number of clusters is determined by an external indicator, the so-called dominance criteria for t-mode principal component analysis. Nevertheless, the resulting partitions are stable for certain numbers of clusters and provide meaningful and reproducible clusters. The resulting types of pressure patterns reveal pronounced long-term variability and various significant trends of the time series of seasonal cluster frequency. Tentative estimations of central European temperature changes based solely on seasonal cluster frequencies can explain between 33.9% (summer) and 59.0% (winter) of temperature variance on the seasonal time scale. However, the signs of long-term changes in temperature are correctly reproduced even on multidecadal–centennial time scales. Moreover, linear warming trends are reproduced, implying from one-third up to one-half of the observed temperature increase between 1851/52 and 2003 (except for summer, but with significant trends for spring and autumn), indicating that changes in daily circulation patterns contribute to the observed overall long-term warming in the central European region.

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H-Y. M. Yeh, N. Prasad, R. Meneghini, W-K. Tao, J. A. Jones, and R. F. Adler

Abstract

Simulations of observations from potential spaceborne radars are made based on storm structure generated from the three-dimensional (3D) Goddard cumulus ensemble model simulation of an intense overland convective system. Five frequencies of 3, 10, 14, 35, and 95 GHz are discussed, but the Tropical Rainfall Measuring Mission precipitation radar sensor frequency ( 14 GHz) is the focus of this study. Radar reflectivities and their attenuation in various atmospheric conditions are studied in this simulation. With the attenuation from cloud and precipitation in the estimation of reflectivity factor (dBZ), the reflectivities in the lower atmosphere in the convective coresare significantly reduced. With spatial resolution of 4 km X 4 km, attenuation at 14 GHz may cause as large as a 20-dBZ difference between the simulated measurements of the peak (Zmp) and near-surface reflectivity (Zmp) in the most intense convective region. The Zmp occurs at various altitudes depending on the hydrometeor concentrations and their vertical distribution. Despite the significant attenuation in the intense cores, the presence of the rain maximum is easily detected by using information of Zmp. In the stratiform region, the attenuation is quite limited (usually less than 5 dBZ), and the reduction of reflectivity is mostly related to the actual vertical structure of cloud distribution. Since Zmp suffers severe attenuation and tends to underestimate surface rainfall intensity in convective regions, Zmp can be more representative for rainfall retrieval in the lower atmosphere in these regions. In the stratiform region where attenuation is negligible, however, Zmp tends to overestimate surface rainfall and Zmp is more appropriate for rainfall retrieval. A hybrid technique using a weight between the two rain intensities is testedand found potentially useful for future applications. The estimated surface rain-rate map based on this hybrid approach captures many of the details of the cloud model rain field but still slightly underestimates the rain-rate maximum.

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A. Anav, P. Friedlingstein, M. Kidston, L. Bopp, P. Ciais, P. Cox, C. Jones, M. Jung, R. Myneni, and Z. Zhu

Abstract

The authors assess the ability of 18 Earth system models to simulate the land and ocean carbon cycle for the present climate. These models will be used in the next Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) for climate projections, and such evaluation allows identification of the strengths and weaknesses of individual coupled carbon–climate models as well as identification of systematic biases of the models. Results show that models correctly reproduce the main climatic variables controlling the spatial and temporal characteristics of the carbon cycle. The seasonal evolution of the variables under examination is well captured. However, weaknesses appear when reproducing specific fields: in particular, considering the land carbon cycle, a general overestimation of photosynthesis and leaf area index is found for most of the models, while the ocean evaluation shows that quite a few models underestimate the primary production.The authors also propose climate and carbon cycle performance metrics in order to assess whether there is a set of consistently better models for reproducing the carbon cycle. Averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles and PDFs from different observed datasets. Although the metrics used in this study allow identification of some models as better or worse than the average, the ranking of this study is partially subjective because of the choice of the variables under examination and also can be sensitive to the choice of reference data. In addition, it was found that the model performances show significant regional variations.

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