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At least 163 records · Page 9

Surface Turbulent Fluxes Over Pack Ice Inferred from TOVS Observations

A one-dimensional, atmospheric boundary layer model is coupled to a thermodynamic ice model to estimate the surface turbulent fluxes over thick sea ice. The principal forcing parameters in this time-dependent model are the air temperature, humidity, and wind speed at a specified level (either at 2 m or at 850 mb) and the downwelling surface radiative fluxes. The free parameters. are the air temperature, humidity, and wind speed profiles below the specified level, the surface skin temperature, the ice temperature profile, and the surface turbulent fluxes. The goal is to determine how well we can estimate the turbulent surface heat and momentum fluxes using forcing parameters from atmospheric temperatures and radiative fluxes retrieved from the TIROS-N Operational Vertical Sounder (TOVS) data. Meteorological observations from the Lead Experiment (LeadEx, April 1992) ice camp are used to validate turbulent fluxes computed with the surface observations and the results are used to compare with estimates based on radio-sonde observations or with estimates based on TOVS data. We find that the TOVS-based estimates of the stress are significantly more accurate than those found with a constant geostrophic drag coefficient, with a root-mean-square error about half as large. This improvement is due to stratification effects included in the boundary layer model. The errors in the sensible heat flux estimates, however, are large compared to the small mean values observed during the field experiment.

Lindsay, R. W.↗

The Role of Combination Techniques in Maximizing the Utility of Precipitation Estimates from Several Multi-Purpose Remote-Sensing Systems

Multi-purpose remote-sensing products from various satellites have proved crucial in developing global estimates of precipitation. Examples of these products include low-earth-orbit and geosynchronous-orbit infrared (leo- and geo-IR), Outgoing Longwave Radiation (OLR), Television Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) data, and passive microwave data such as that from the Special Sensor Microwave/ Imager (SSM/I). Each of these datasets has served as the basis for at least one useful quasi-global precipitation estimation algorithm; however, the quality of estimates varies tremendously among the algorithms for the different climatic regions around the globe.

Huffman, George J.↗

Dynamical and chemical contributions to variability in microwave limb sounder Arctic stratoshperic column ozone

Analyses of column ozone above 100 hPa (Col100) derived from Upper Atmosphere Research Satellite Microwave Limb Sounder (MLS) data in February/March 1992-1998 show that about half of the interannual variability in Col100 in the Arctic polar vortex in late winter results from interannual variability in chemical loss. A majority of the remainder results from interannual variability in day-to-day dynamical motions including adiabatic warming/cooling and poleward advection of underlying upper tropospheric subtropical air on short timescales, rather than from variations in descent rates and large-scale transport over the winters. The morphology of Col100 from MLS remains very similar to that in the dynamical models even in the years with most chemical ozone loss. The amount and character of day-to-day variability in dynamical models closely follows that in MLS Col100. Although the morphology of and day-to-day variability in Arctic column ozone are controlled by dynamical processes, chemical ozone loss was a major factor in producing both the low values of and the large interannual variability in Arctic column ozone observed during the 1990s.

Arctic ozone loss↗

Regulation of H2O and CO in Tropical Tropopause Layer by the Madden-Julian Oscillation

Impacts of the Madden-Julian oscillation (MJO) on the water vapor (H2O) and carbon monoxide (CO) abundances in the tropical tropopause layer (TTL) are investigated using Aura Microwave Limb Sounder (MLS) data for November 2004 to May 2005. The effects of the eastward propagation of MJO on H2O and CO abundances in the TTL are evident. Deep convection transports H20 into the upper troposphere up to about the 355-365 K level. Around the 365-375 K level, a dry anomaly is collocated with a cold anomaly, which is above a warm anomaly located near the region of convection enhancement. Tropical mean H20 at 375 K is regulated by the MJO through convection enhancement and coherent with the local MJO-related temperature variation. The locations of dehydration follow the eastward propagation of convection enhancement and its area extent depends on the phase of the MJO. Enhancement of deep convection associated with the MJO also injects CO from the lower troposphere to the TTL up to 375 K. However, tropical mean CO at 375 K responds instantaneously to the large injection event occurring over the African continent.

Wong, Sun↗

Modeling the Frozen-In Anticyclone in the 2005 Arctic Summer Stratosphere

Immediately following the breakup of the 2005 Arctic spring stratospheric vortex, a tropical air mass, characterized by low potential vorticity (PV) and high nitrous oxide (N2O), was advected poleward and became trapped in the easterly summer polar vortex. This feature, known as a "Frozen-In Anticyclone (FrIAC)", was observed in Earth Observing System (EOS) Aura Microwave Limb Sounder (MLS) data to span the potential temperature range from approximately 580 to 1100 K (approximately 25 to 40 km altitude) and to persist from late March to late August 2005. This study compares MLS N2O observations with simulations from the Global Modeling Initiative (GMI) chemistry and transport model, the GEOS-5/MERRA Replay model, and the VanLeer Icosahedral Triangular Advection isentropic transport model to elucidate the processes involved in the lifecycle of the FrIAC which is here divided into three distinct phases. During the "spin-up phase" (March to early April), strong poleward flow resulted in a tight isolated anticyclonic vortex at approximately 70-90 deg N, marked with elevated N2O. GMI, Replay, and VITA all reliably simulted the spin-up of the FrIAC, although the GMI and Replay peak N2O values were too low. The FrIAC became trapped in the developing summer easterly flow and circulated around the polar region during the "anticyclonic phase" (early April to the end of May). During this phase, the FrIAC crossed directly over the pole between the 7th and 14th of April. The VITA and Replay simulations transported the N2O anomaly intact during this crossing, in agreement with MLS, but unrealistic dispersion of the anomaly occurred in the GMI simulation due to excessive numerical mixing of the polar cap. The vortex associated with the FrIAC was apparently resistant to the weak vertical hear during the anticyclonic phase, and it thereby protected the embedded N20 anomaly from stretching. The vortex decayed in late May due to diabatic processes, leaving the N2O anomaly exposed to horizontal and vertical wind shears during the "shearing phase" (June to August). The observed lifetime of the FrIAC during this phase is consistent with time-scales calculated from the ambient horizontal and vertical wind shear. Replay maintained the horizontal structure of the N2O anomaly similar to NILS well into August. The VITA simulation also captured the horizontal structure of the FrIAC during this phase, but VITA eventually developed fine-scale N2O structure not observed in MLS data.

Allen, D. R.↗

Using Open and Interoperable Ways to Publish and Access LANCE AIRS Near-Real Time Data

The Atmospheric Infrared Sounder (AIRS) Near-Real Time (NRT) data from the Land Atmosphere Near real-time Capability for EOS (LANCE) element at the Goddard Earth Sciences Data and Information Services Center (GES DISC) provides information on the global and regional atmospheric state, with very low temporal latency, to support climate research and improve weather forecasting. An open and interoperable platform is useful to facilitate access to, and integration of, LANCE AIRS NRT data. As Web services technology has matured in recent years, a new scalable Service-Oriented Architecture (SOA) is emerging as the basic platform for distributed computing and large networks of interoperable applications. Following the provide-register-discover-consume SOA paradigm, this presentation discusses how to use open-source geospatial software components to build Web services for publishing and accessing AIRS NRT data, explore the metadata relevant to registering and discovering data and services in the catalogue systems, and implement a Web portal to facilitate users' consumption of the data and services.

Zhao, Peisheng↗

Convective Entrainment Rates Estimated from Aura CO and CloudSat/CALIPSO Observations and Comparison with GEOS-5

Entrainment rate (λ) in convective parameterizations remains a sensitive parameter with much uncertainty in model simulations. This study estimates λ using carbon monoxide (CO) measurements jointly from the Microwave Limb Sounder (MLS) and Tropospheric Emission Spectrometer (TES) onboard the Aura satellite, associated with deep convective cases identified by CloudSat and CALIPSO observations. CO is treated as a conserved quantity over convective transport time scales and a simple entraining-plume model is used to derive entrainment rates. The relationships of the observational estimates of λ as a function of convective height, environmental relative humidity and convective available potential energy (CAPE) derived from Atmospheric Infrared Sounder (AIRS) data are compared with those from Goddard Earth Observing System Model (GEOS-5) simulations. Bulk statistics of λ show that the values of λ are predominately below 20% km(exp-1) for deep convection and the occurrence frequency of any λ decreases with increasing λ. Composite λ values are generally lower in the tropics compared to northern mid-latitudes in both observations and the GEOS-5 model. A decrease of λ with increasing convective height is found in both observations and model simulations. We also find that λ tends to decrease with increasing CAPE in the observation-based λ’s and plume-based GEOS-5 λ’s, although the model given λ’s have a non-monotonic relation with CAPE. The observed λ’s have a weak relation with lower-to-mid tropospheric RH, while both GEOS-5 plume-based and given λ increases with increasing RH.

Ryan E Stanfield↗

Quantifying and Characterizing Striping of Microwave Humidity Sounder with Observation and Simulation

Striping has been observed in the MetOp-A Microwave Humidity Sounder (MHS) data since its degradation in November 2018. However, accurate striping quantification and characterization remain challenging due to the large scene dynamics observed at W/G bands of MHS. Here we have developed a set of novel algorithms for striping quantification, decomposition, characterization, and simulation. Our algorithm extracts striping from the warm-load and cold-space scenes that are relatively stable. We break down the striping into two parts of thermal and 1/f noise and quantify their absolute magnitude and relative ratio. We found a significant increase in striping at 157 GHz that has more than quadrupled by October 2019 relative to its normal level. Regardless of the degradation, the ratio of thermal and 1/f noise remains the same. Our simulation reproduces all the characteristics of striping against observation. It is shown that 1/f noise generates sharp, non-periodic stripes, while thermal noise also generates stripes but with smoother band features. The latter is due to the periodic calibration that has a chopping effect. The striping percentage, defined as the ratio of 1/f to total noise, shows no dependence on the scene temperature. Striping is pronounced not only in 157 GHz but also in 89 and190 GHz with the striping percentage over 50%, while lower in183 GHz of 20%. The results provide insights for quantifying and understanding striping. Our algorithm can be applied to other radiometers and to simulate striping for evaluating its impact in data assimilation and science products.

John Xun Yang↗

Bridging Current Indirect and Future Direct Estimates of Convective Mass Flux Toward Quantifying the Role of Convective Cores on Anvil Area Time Tendencies

Anvil cloud spatial extent is strongly driven by convective mass flux. However, the lack of convective mass flux observations precludes global analyses of the functional relationship between anvil cloud area growth tendencies and convective areal coverage and vertical mass flux. Partly informed by analyses of a hierarchy of WRF mesoscale convective system (MCS) simulations, in this presentation, we discuss new work on estimating convective mass flux by way of an approach that casts the problem of quantifying convective mass flux into terms related to diabatic heating vertical structure, convective area and tropospheric stability. We demonstrate the usefulness of this approach at the MCS spatial scale via development of a simple, robust model that analytically connects system-scale convective mass flux and anvil cloud area growth rates. We show that the model predicts anvil area size changes in agreement with those observed in a global convective system tracking database (TOOCAN). An additional advantage of this approach for estimating convective mass flux is that it bridges future satellite mission plans for directly observing convective mass flux (e.g., AOS) with longer-record observations made by TRMM, GPM and satellite sounder mission data (the latter used for estimating stability) that, when combined, can be used for inferring convective mass fluxes at the MCS spatial scale spanning slowly changing, diverse environments. An evaluation and bridging of both direct and indirect approaches supports convective process analyses varying over longer time periods in this “era of convection.”

convective mass flux↗

Bridging current indirect and future direct estimates of convective mass flux toward quantifying the role of convective cores on anvil area time tendencies

Anvil cloud spatial extent is strongly driven by convective mass flux. However, the lack of convective mass flux observations precludes global analyses of the functional relationship between anvil cloud area growth tendencies and convective areal coverage and vertical mass flux. Partly informed by analyses of a hierarchy of WRF mesoscale convective system (MCS) simulations, in this presentation, we discuss new work on estimating convective mass flux by way of an approach that casts the problem of quantifying convective mass flux into terms related to diabatic heating vertical structure, convective area and tropospheric stability. We demonstrate the usefulness of this approach at the MCS spatial scale via development of a simple, robust model that analytically connects system-scale convective mass flux and anvil cloud area growth rates. We show that the model predicts anvil area size changes in agreement with those observed in a global convective system tracking database (TOOCAN). An additional advantage of this approach for estimating convective mass flux is that it bridges future satellite mission plans for directly observing convective mass flux (e.g., AOS) with longer-record observations made by TRMM, GPM and satellite sounder mission data (the latter used for estimating stability) that, when combined, can be used for inferring convective mass fluxes at the MCS spatial scale spanning slowly changing, diverse environments. An evaluation and bridging of both direct and indirect approaches supports convective process analyses varying over longer time periods in this “era of convection.”

convective mass flux↗

Pressure Deficit in Gale Crater and a Larger Northern Polar Cap After the MY34 Global Dust Storm

We describe the model-independent analysis technique of Mars Science Laboratory (MSL) pressure and Mars Climate Sounder (MCS) data in de la Torre Juárez et al. (2019, https://doi.org/10.22541/essoar.169945479.90436599/v1) that compared multiple years of surface pressures on Gale before, during, and after the Global Dust Storm of Mars Year 34. The analysis found (a) representative pressure scale heights over Gale; (b) that the storm was followed by a pressure deficit at Gale; (c) the following C storms did not eliminate the deficit; (d) changes in the duration of the polar caps condensation seasons, with an early start of the North Polar (NP) ice cap growing season the year before the Great Dust Storm (GDS) and a late signature of the end of the expansion season thereafter, changes consistent with a larger growth phase of the NP cap; (e) MCS observed a larger than usual NP cap; and (f) cold temperature anomalies over the NP and warm over the Southern Pole after the storm. We also show that the analysis of observed MSL pressure data alone filters out effects on the pressure signal that are attributable to dynamical and orographic processes in a recent model analysis that makes similar interpretations as our 2019 study. One additional Mars year of observations is included to eliminate early concerns about sensor drifts. Noting that a similar NP anomaly was observed with MCS data after the last early GDS in MY25, and not the later GDS of MY27, the results suggest a possible unique effect of early GDSs.

Manuel de la Torre Juárez↗

Statistical analysis and use of VAS radiance data

Researchers goals are to describe the information content of Vertical Atmospheric Sounder (VAS) radiance data, especially the 6.7 micrometers water vapor channel, to better interpret the atmosphere's water vapor structure from 6.7 micrometers imagery, and to investigate new analysis and forecasting techniques utilizing retrieved VAS soundings. Researchers made major progress toward these goals during FY-85. They are investigating 6.7 micrometer imagery on 6 to 7 March 1982, a day when special mesoscale ground truth data were collected during the 1982 atmospheric variability experiment/vertical amospheric sounder (AVE/VAS) field experiment. A dark (dry) image streak having mesoscale details was located over the special data region, and it provides the major focus of the case study. Mesoscale radiosonde-derived humidity data are found to verify fine scale features of the image that are not evident from the standard National Weather Service network. Thus, VAS imagery is a reliable detector of mesoscale moisture structure during this case. To investigate causes for the image streak, researchers are calculating water vapor budgets. Subsidence is found to be a factor in the current case as well; however, patterns of descent are not related to the jet streak according to traditional conceptual models. Thus, it appears that more research into jet stream dynamics is needed in order to better interpret 6.7 micrometer imagery.

Fuelberg, H. E.↗

Mesospheric effects of solar ultraviolet variations - Further analysis of SME IR ozone and Nimbus 7 SAMS temperature data

In order to improve the constraints on models of the mesospheric response to solar UV variations, an analysis is conducted of the Solar Mesosphere Explorer (SME) IR ozone data and Nimbus 7 stratosphere and mesosphere sounder (SAMS) temperature data. Maximum low-altitude ozone and temperature-response amplitudes occur at about the same altitude, where a strong coupling between photochemical and thermal components of the mesospheric response is suggested by the simultaneous positive temperature and negative ozone response maxima. Increased Lyman-alpha dissociation of water vapor and temperature feedback are theorized to account for the negative ozone response. HO(x) chemical heating can increase as ozone destruction increases, and can therefore account for the positive temperature response.

Hood, L. L.↗

Dynamic and static initialization of a mesoscale model using VAS satellite data

Various combinations of temperature and moisture data from the VISSR Atmospheric Sounder (VAS), conventional radiosonde data, and National Meteorological Center (NMC) global analysis, were used in a successive-correction type of objective-analysis procedure to produce analyses for 1200 GMT. The NMC global analyses served as the first-guess field for all of the objective analysis procedures. The first-guess field was enhanced by radiosonde data alone, VAS data alone, both radiosonde and VAS data, or by neither data source. In addition, two objective analyses were used in a dynamic initialization: one included only radiosonde data and the other used both radiosonde and VAS data. The dependence of 12 hour forecast skill on data type and the methods by which the data were used in the analysis/initialization were then investigated. This was done by comparison of forecast and observed fields, of sea-level pressure, temperature, wind, moisture, and accumulated precipitation. The use of VAS data in the initial conditions had a slight positive impact upon forecast temperature and moisture but a negative impact upon forecast wind. This was true for both the static and dynamic initialization experiments. Precipitation forecasts from all of the model simulations were nearly the same.

Beauchamp, James G.↗

Space-Time Data Fusion

Space-time Data Fusion (STDF) is a methodology for combing heterogeneous remote sensing data to optimally estimate the true values of a geophysical field of interest, and obtain uncertainties for those estimates. The input data sets may have different observing characteristics including different footprints, spatial resolutions and fields of view, orbit cycles, biases, and noise characteristics. Despite these differences all observed data can be linked to the underlying field, and therefore the each other, by a statistical model. Differences in footprints and other geometric characteristics are accounted for by parameterizing pixel-level remote sensing observations as spatial integrals of true field values lying within pixel boundaries, plus measurement error. Both spatial and temporal correlations in the true field and in the observations are estimated and incorporated through the use of a space-time random effects (STRE) model. Once the models parameters are estimated, we use it to derive expressions for optimal (minimum mean squared error and unbiased) estimates of the true field at any arbitrary location of interest, computed from the observations. Standard errors of these estimates are also produced, allowing confidence intervals to be constructed. The procedure is carried out on a fine spatial grid to approximate a continuous field. We demonstrate STDF by applying it to the problem of estimating CO2 concentration in the lower-atmosphere using data from the Atmospheric Infrared Sounder (AIRS) and the Japanese Greenhouse Gasses Observing Satellite (GOSAT) over one year for the continental US.

Greenhouse Gases Observing Satellite (GOSAT)↗