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M. J. Bailey, A. O'Neill, and V. D. Pope

Abstract

Since late 1978, the U.K. Meteorological Office (UKMO) has processed accurate radiance measurements of the stratosphere from a set of three radiometers (Statospheric Sounding Unit, Microwave Sounding Unit, High-Resolution Infrared Sounder) flown on satellites in the TIROS series. The radiometers scan both sides of the subsatellite track giving almost global coverage. UKMO uses its own retrieval algorithm to derive thickness from radiances. The retrieval is a linear, physiral–statistical method that utilizes a reference set of temperature profiles as a priori data. Thickness are added to a contemporaneous field of geopotential height at 100 hPa to give geopotential heights at standard pressure levels in the stratosphere up to 1 hPa. Global synoptic fields for 1200 UTC are produced every day on a regular latitude–longitude grid by linear interpolation in space and time. The paper describes the retrieval method and objective analysis in detail. It outlines the availability of data in the 14-year archive and summarizes the main findings of several studies on data quality. Finally, it tells prospective users how to get the data and what cheeks they should make before trying to interpret them.

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J. Gourrion, D. Vandemark, S. Bailey, B. Chapron, G. P. Gommenginger, P. G. Challenor, and M. A. Srokosz

Abstract

Globally distributed crossovers of altimeter and scatterometer observations clearly demonstrate that ocean altimeter backscatter correlates with both the near-surface wind speed and the sea state. Satellite data from TOPEX/Poseidon and NSCAT are used to develop an empirical altimeter wind speed model that attenuates the sea-state signature and improves upon the present operational altimeter wind model. The inversion is defined using a multilayer perceptron neural network with altimeter-derived backscatter and significant wave height as inputs. Comparisons between this new model and past single input routines indicates that the rms wind error is reduced by 10%–15% in tandem with the lowering of wind error residuals dependent on the sea state. Both model intercomparison and validation of the new routine are detailed, including the use of large independent data compilations that include the SeaWinds and ERS scatterometers, ECMWF wind fields, and buoy measurements. The model provides consistent improvement against these varied sources with a wind-independent bias below 0.3 m s−1. The continuous form of the defined function, along with the global data used in its derivation, suggest an algorithm suitable for operational application to Ku-band altimeters. Further model improvement through wave height inclusion is limited due to an inherent multivaluedness between any single realization of the altimeter measurement pair [σ o, H S] and observed near-surface winds. This ambiguity indicates that H S is a limited proxy for variable gravity wave properties that impact upon altimeter backscatter.

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C. M. Bitz, K. M. Shell, P. R. Gent, D. A. Bailey, G. Danabasoglu, K. C. Armour, M. M. Holland, and J. T. Kiehl

Abstract

Equilibrium climate sensitivity of the Community Climate System Model, version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. This study uses the radiative kernel technique to show that, from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude and the shortwave cloud feedback increases. These two warming effects are partially canceled by cooling because of slight decreases in the global mean water vapor feedback and longwave cloud feedback from CCSM3 to CCSM4.

A new formulation of the mixed layer, slab-ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab-ocean model version for both CCSM3 and CCSM4. The authors argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.

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W. J. Koshak, R. J. Solakiewicz, R. J. Blakeslee, S. J. Goodman, H. J. Christian, J. M. Hall, J. C. Bailey, E. P. Krider, M. G. Bateman, D. J. Boccippio, D. M. Mach, E. W. McCaul, M. F. Stewart, D. E. Buechler, W. A. Petersen, and D. J. Cecil

Abstract

Two approaches are used to characterize how accurately the north Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA Marshall Space Flight Center (MSFC) and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix Theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50 ns, but all other possible errors (e.g., anomalous VHF noise sources) are neglected. The detailed spatial distributions of retrieval errors are provided. Even though the two methods are independent of one another, they nevertheless provide remarkably similar results. However, altitude error estimates derived from the two methods differ (the Monte Carlo result being taken as more accurate). Additionally, this study clarifies the mathematical retrieval process. In particular, the mathematical difference between the first-guess linear solution and the Marquardt-iterated solution is rigorously established thereby explaining why Marquardt iterations improve upon the linear solution.

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Anders A. Jensen, James O. Pinto, Sean C. C. Bailey, Ryan A. Sobash, Gijs de Boer, Adam L. Houston, Phillip B. Chilson, Tyler Bell, Glen Romine, Suzanne W. Smith, Dale A. Lawrence, Cory Dixon, Julie K. Lundquist, Jamey D. Jacob, Jack Elston, Sean Waugh, and Matthias Steiner

Abstract

Uncrewed aircraft system (UAS) observations collected during the 2018 LAPSE-RATE field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting model using an ensemble Kalman filter. The benefit of UAS observations was assessed for a terrain-driven (drainage and upvalley) flow event that occurred within Colorado’s San Luis Valley (SLV) using independent observations. The analysis and prediction of the strength, depth and horizontal extent of drainage flow from the Saguache Canyon and the subsequent transition to upvalley and up-canyon flow was improved compared to that obtained both without DA (benchmark) and when only surface observations were assimilated. Assimilation of UAS observations greatly improved the analyses of vertical variations in temperature, relative humidity, and winds at multiple locations in the northern portion of the SLV with reductions in both bias and the root mean square error of roughly 40% for each variable compared to the benchmark run. Despite these noted improvements, some biases remain that were tied to measurement error and/or the impact of the boundary layer parameterization on vertically spreading the observations, both of which require further exploration. The results presented here highlight how observations obtained with a fleet of profiling UAS improve limited-area, high-resolution analyses and short-term forecasts in complex terrain.

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