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E. J. Barton, C. M. Taylor, C. Klein, P. P. Harris, and X. Meng

Abstract

Convection over the Tibetan Plateau (TP) has been linked to heavy rain and flooding in downstream parts of China. Understanding processes which influence the development of convection on the TP could contribute to better forecasting of these extreme events. TP scale (~1000 km) soil moisture gradients have been shown to influence formation of convective systems over the eastern TP. The importance of smaller-scale (~10 km) variability has been identified in other regions (including the Sahel and Mongolia) but has yet to be investigated for the TP. In addition, compared to studies over flat terrain, much less is known about soil moisture–convection feedbacks above complex topography. In this study we use satellite observations of cold cloud, land surface temperature, and soil moisture to analyze the effect of mesoscale soil moisture heterogeneity on the initiation of strong convection in the complex TP environment. We find that strong convection is favored over negative (positive) land surface temperature (soil moisture) gradients. The signal is strongest for less vegetation and low topographic complexity, though still significant up to a local standard deviation of 300 m in elevation, accounting for 65% of cases. In addition, the signal is dependent on background wind. Strong convective initiation is only sensitive to local (tens of kilometers) soil moisture heterogeneity for light wind speeds, though large-scale (hundreds of kilometers) gradients may still be important for strong wind speeds. Our results demonstrate that, even in the presence of complex topography, local soil moisture variability plays an important role in storm development.

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C. J. Donlon, S. J. Keogh, D. J. Baldwin, I. S. Robinson, I. Ridley, T. Sheasby, I. J. Barton, E. F. Bradley, T. J. Nightingale, and W. Emery

Abstract

Satellite sea surface skin temperature (SSST) maps are readily available from precisely calibrated radiometer systems such as the ERS along-track scanning radiometer and, in the near future, from the moderate-resolution imaging spectroradiometer. However, the use of subsurface bulk sea surface temperature (BSST) measurements as the primary source of in situ data required for the development of new sea surface temperature algorithms and the accurate validation of these global datasets is questionable. This is because BSST measurements are not a measure of the sea surface skin temperature, which is actually observed by a satellite infrared radiometer. Consequently, the use of BSST data for validation and derivation of satellite derived “pseudo-BSST” and SSST datasets will limit their accuracy to at least the rms deviation of the BSST–SSST difference, typically about ±0.5 K. Unfortunately, the prohibitive cost and difficulty of deploying infrared radiometers at sea has prevented the regular collection of a comprehensive global satellite SSST validation dataset. In response to this situation, an assessment of the TASCO THI-500L infrared radiometer system as a potential candidate for the widespread validation of satellite SSST observations is presented. This is a low-cost, broadband radiometer that has been commonly deployed in the field to measure SSST by several research groups. A comparison between SSST derived from TASCO THI-500L measurements and contemporaneous scanning infrared sea surface temperature radiometer measurements, which are accurate to better than 0.1 K, demonstrates low bias (0.1 K) and rms (0.08 K) differences between the two instruments. However, to achieve this accuracy, the TASCO THI-500L radiometer must be deployed with care to ensure that the radiometer fore-optics are kept free of salt water contamination and shaded from direct sunlight. When this is done, this type of low-cost radiometer system could form the core of a global SSST validation program.

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Matthew A. Janiga, Carl J. Schreck III, James A. Ridout, Maria Flatau, Neil P. Barton, E. Joseph Metzger, and Carolyn A. Reynolds

Abstract

In this study, the contribution of low-frequency (>100 days), Madden–Julian oscillation (MJO), and convectively coupled equatorial wave (CCEW) variability to the skill in predicting convection and winds in the tropics at weeks 1–3 is examined. We use subseasonal forecasts from the Navy Earth System Model (NESM); NCEP Climate Forecast System, version 2 (CFSv2); and ECMWF initialized in boreal summer 1999–2015. A technique for performing wavenumber–frequency filtering on subseasonal forecasts is introduced and applied to these datasets. This approach is better able to isolate regional variations in MJO forecast skill than traditional global MJO indices. Biases in the mean state and in the activity of the MJO and CCEWs are smallest in the ECMWF model. The NESM overestimates cloud cover as well as MJO, equatorial Rossby, and mixed Rossby–gravity/tropical depression activity over the west Pacific. The CFSv2 underestimates convectively coupled Kelvin wave activity. The predictive skill of the models at weeks 1–3 is examined by decomposing the forecasts into wavenumber–frequency signals to determine the modes of variability that contribute to forecast skill. All three models have a similar ability to simulate low-frequency variability but large differences in MJO skill are observed. The skill of the NESM and ECMWF model in simulating MJO-related OLR signals at week 2 is greatest over two regions of high MJO activity, the equatorial Indian Ocean and Maritime Continent, and the east Pacific. The MJO in the CFSv2 is too slow and too weak, which results in lower MJO skill in these regions.

Open access
C. Donlon, I. Robinson, K. S. Casey, J. Vazquez-Cuervo, E. Armstrong, O. Arino, C. Gentemann, D. May, P. LeBorgne, J. Piollé, I. Barton, H. Beggs, D. J. S. Poulter, C. J. Merchant, A. Bingham, S. Heinz, A. Harris, G. Wick, B. Emery, P. Minnett, R. Evans, D. Llewellyn-Jones, C. Mutlow, R. W. Reynolds, H. Kawamura, and N. Rayner

A new generation of integrated sea surface temperature (SST) data products are being provided by the Global Ocean Data Assimilation Experiment (GODAE) High-Resolution SST Pilot Project (GHRSST-PP). These combine in near-real time various SST data products from several different satellite sensors and in situ observations and maintain the fine spatial and temporal resolution needed by SST inputs to operational models. The practical realization of such an approach is complicated by the characteristic differences that exist between measurements of SST obtained from subsurface in-water sensors, and satellite microwave and satellite infrared radiometer systems. Furthermore, diurnal variability of SST within a 24-h period, manifested as both warm-layer and cool-skin deviations, introduces additional uncertainty for direct intercomparison between data sources and the implementation of data-merging strategies. The GHRSST-PP has developed and now operates an internationally distributed system that provides operational feeds of regional and global coverage high-resolution SST data products (better than 10 km and ~6 h). A suite of online satellite SST diagnostic systems are also available within the project. All GHRSST-PP products have a standard format, include uncertainty estimates for each measurement, and are served to the international user community free of charge through a variety of data transport mechanisms and access points. They are being used for a number of operational applications. The approach will also be extended back to 1981 by a dedicated reanalysis project. This paper provides a summary overview of the GHRSST-PP structure, activities, and data products. For a complete discussion, and access to data products and services see the information online at www.ghrsst-pp.org.

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