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1. A Global Perspective of Tropical Cyclone Precipitation in Reanalyses

   https://doi.org/10.1175/JCLI-D-20-0892.1  

   Jones, Evan ; Wing, Allison A. ; Parfitt, Rhys ( November 2021 , Journal of Climate)

   Abstract This study compares the spread in climatological tropical cyclone (TC) precipitation across eight different reanalysis datasets: NCEP-CFSR, ERA-20C, ERA-40, ERA5, ERA-Interim, JRA-55, MERRA-2, and NOAA-20C. TC precipitation is assigned using manual tracking via a fixed 500-km radius from each TC center. The reanalyses capture similar general spatial patterns of TC precipitation and TC precipitation fraction, defined as the fraction of annual precipitation assigned to TCs, and the spread in TC precipitation is larger than the spread in total precipitation across reanalyses. The spread in TC precipitation relative to the inter-reanalysis mean TC precipitation, or relative spread, is larger in the east Pacific than in the west Pacific. Partitioned by reanalysis intensity, the largest relative spread across reanalyses in TC precipitation is from high-intensity TCs. In comparison with satellite observations, reanalyses show lower climatological mean annual TC precipitation over most areas. A comparison of area-averaged precipitation rate in TCs composited over reanalysis intensity shows the spread across reanalyses is larger for higher intensity TCs. Testing the sensitivity of TC precipitation assignment to tracking method shows that climatological mean annual TC precipitation is systematically larger when assigned via manual tracking versus objective tracking. However, this tendency is minimized when TC precipitation is normalized by TC density. Overall, TC precipitation in reanalyses is affected by not only horizontal output resolution or any TC preprocessing, but also data assimilation and parameterization schemes. The results indicate that improvements in the representation of TCs and their precipitation in reanalyses are needed to improve overall precipitation. 

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2. Wind Stress, Wind Stress Curl, and Upwelling Velocities in the Northwest Atlantic (80-45W, 30-45N) during 1980-2019

   https://doi.org/10.5281/zenodo.8200832  

   Gifford, Ian ; Gangopadhyay, Avijit ; Andres, Magdalena ; Gawarkiewicz, Glen ; Oliver, Hilde ; Silver, Adrienne ( January 2023 , Zenodo)

   This dataset contains three netcdf files that pertain to monthly, seasonal, and annual fields of surface wind stress, wind stress curl, and curl-derived upwelling velocities over the Northwest Atlantic (80-45W, 30-45N) covering a forty year period from 1980 to 2019. Six-hourly surface (10 m) wind speed components from the Japanese 55-year reanalysis (JRA-55; Kobayashi et al., 2015) were processed from 1980 to 2019 over a larger North Atlantic domain of 100W to 10E and 10N to 80N. Wind stress was computed using a modified step-wise formulation, originally based on (Gill, 1982) and a non-linear drag coefficient (Large and Pond, 1981), and later modified for low speeds (Trenberth et al., 1989). See Gifford (2023) for more details.   

   After the six-hourly zonal and meridional wind stresses were calculated, the zonal change in meridional stress (curlx) and the negative meridional change in zonal stress (curly) were found using NumPy’s gradient function in Python (Harris et al., 2020) over the larger North Atlantic domain (100W-10E, 10-80N). The curl (curlx + curly) over the study domain (80-45W, 10-80N) is then extracted, which maintain a constant order of computational accuracy in the interior and along the boundaries for the smaller domain in a centered-difference gradient calculation. 

   The monthly averages of the 6-hour daily stresses and curls were then computed using the command line suite climate data operators (CDO, Schulzweida, 2022) monmean function. The seasonal (3-month average) and annual averages (12-month average) were calculated in Python using the monthly fields with NumPy (NumPy, Harris et al., 2020). 

   Corresponding upwelling velocities at different time-scales were obtained from the respective curl fields and zonal wind stress by using the Ekman pumping equation of the study by Risien and Chelton (2008; page 2393). Please see Gifford (2023) for more details.   

   The files each contain nine variables that include longitude, latitude, time, zonal wind stress, meridional wind stress, zonal change in meridional wind stress (curlx), the negative meridional change in zonal wind stress (curly), total curl, and upwelling. Units of time begin in 1980 and are months, seasons (JFM etc.), and years to 2019. The longitude variable extends from 80W to 45W and latitude is 30N to 45N with uniform 1.25 degree resolution.  

   Units of stress are in Pascals, units of curl are in Pascals per meter, and upwelling velocity is described by centimeters per day. The spatial grid is a 29 x 13 longitude x latitude array. 

   Filenames: 

   monthly_windstress_wsc_upwelling.nc: 480 time steps from 80W to 45W and 30N to 45N.

   seasonal_windstress_wsc_upwelling.nc: 160 time steps from 80W to 45W and 30N to 45N.

   annual_windstress_wsc_upwelling.nc: 40 time steps from 80W to 45W and 30N to 45N.

   Please contact igifford@earth.miami.edu for any queries. {"references": ["Gifford, I.H., 2023. The Synchronicity of the Gulf Stream Free Jet and the Wind Induced Cyclonic Vorticity Pool. MS Thesis, University of Massachusetts Dartmouth. 75pp.", "Gill, A. E. (1982). Atmosphere-ocean dynamics (Vol. 30). Academic Press.", "Harris, C.R., Millman, K.J., van der Walt, S.J. et al. Array programming with NumPy. Nature 585, 357\u2013362 (2020). DOI: 10.1038/s41586-020-2649-2.", "Japan Meteorological Agency/Japan (2013), JRA-55: Japanese 55-year Reanalysis, Daily 3-Hourly and 6-Hourly Data, https://doi.org/10.5065/D6HH6H41, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, Colo. (Updated monthly.)", "Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H. and Miyaoka, K., 2015. The JRA-55 reanalysis: General specifications and basic characteristics.\u202fJournal of the Meteorological Society of Japan. Ser. II,\u202f93(1), pp.5-48.", "Large, W.G. and Pond, S., 1981. Open ocean momentum flux measurements in moderate to strong winds.\u202fJournal of physical oceanography,\u202f11(3), pp.324-336.", "Risien, C.M. and Chelton, D.B., 2008. A global climatology of surface wind and wind stress fields from eight years of QuikSCAT scatterometer data.\u202fJournal of Physical Oceanography,\u202f38(11), pp.2379-2413.", "Schulzweida, Uwe. (2022). CDO User Guide (2.1.0). Zenodo. https://doi.org/10.5281/zenodo.7112925.", "Trenberth, K.E., Large, W.G. and Olson, J.G., 1989. The effective drag coefficient for evaluating wind stress over the oceans.\u202fJournal of Climate,\u202f2(12), pp.1507-1516."]} 

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3. Monthly and Annual contour lines of the zero and the positive maximum of the Wind Stress Curl over Western North Atlantic during 1980-2019 and the Gulf Stream path during 1993-2019.

   https://doi.org/10.5281/zenodo.8217388  

   Gifford, Ian ; Silver, Adrienne ; Gangopadhyay, Avijit ; Andres, Magdalena ; Gawarkiewicz, Glen ; Oliver, Hilde ( January 2023 , Zenodo)

   This dataset includes multiple fields: (i) files for monthly and annual fields for the max curl line and the zero curl line at 0.1 degree longitudinal resolutions; (ii) files for monthly and annual GS path obtained from Altimetry and originally processed by Andres (2016) at 0.1 degree longitudinal resolution. The maximum curl line (MCL) and the zero curl line (ZCL) calculations are briefly described here and are based on the original wind data (at 1.25 x 1.25 degree) provided by the Japanese reanalysis (JRA-55; Kobayashi et al., 2015) and available at https://zenodo.org/record/8200832 (Gifford et al. 2023). For details see Gifford, 2023. 

   The wind stress curl (WSC) fields used for the MCL and ZCL calculations extend from 80W to 45W and 30N to 45N at the 1.25 by 1.25-degree resolution.  The MCL is defined as the maximum WSC values greater than zero within the domain per 1.25 degree longitude. As such, it is a function of longitude and is not a constant WSC value unlike the zero contour. High wind stress curl values that occurred near the coast were not included within this calculation. After MCL at the 1.25 resolution was obtained the line was smoothed with a gaussian smoothing and interpolated on to a 0.1 longitudinal resolution. The smoothed MCL lines at 0.1 degree resolution are provided in separate files for monthly and annual averages (2 files). Similarly, 2 other files (monthly and annual) are provided for the ZCL.    

   Like the MCL, the ZCL is a line derived from 1.25 degree longitude throughout the domain under the condition that it's the line of zero WSC. The ZCL is constant at 0 and does not vary spatially like the MCL. If there are more than one location of zero curl for a given longitude the first location south of the MCL is selected. Similar to the MCL, the ZCL was smoothed with a gaussian smoothing and interpolated on to a 0.1 longitudinal resolution.   

   The above files span the years from 1980 through 2019. So, the monthly files have 480 months starting January 1980, and the annual files have 40 years of data. The files are organized with each row being a new time step and each column being a different longitude. Therefore, the monthly MCL and ZCL files are each 480 x 351 for the 0.1 resolution data. Similarly, the annual files are 40 x 351 for the 0.1 degree resolution data.  

   Note that the monthly MCLs and ZCLs are obtained from the monthly wind-stress curl fields. The annual MCLs and ZCLs are obtained from the annual wind-stress curl fields.

   Since the monthly curl fields preserves more atmospheric mesoscales than the annual curl fields, the 12-month average of the monthly MCLs and ZCLs will not match with the annual MCLs and ZCLs derived from the annual curl field.  The annual MCLs and ZCLs provided here are obtained from the annual curl fields and representative metrics of the wind forcing on an annual time-scale. 

   Furthermore, the monthly Gulf Stream axis path (25 cm isoheight from Altimeter, reprocessed by Andres (2016) technique) from 1993 through 2019 have been made available here. A total of 324 monthly paths of the Gulf Stream are tabulated. In addition, the annual GS paths for these 27 years (1993-2019) of altimetry era have been put together for ease of use. The monthly Gulf Stream paths have been resampled and reprocessed for uniqueness at every 0.1 degree longitude from 75W to 50W and smoothed with a 100 km (10 point) running average via matlab. The uniqueness has been achieved by using Consolidator algorithm (D’Errico, 2023). 

   Each monthly or annual GS path has 251 points between 75W to 50W at 0.1 degree resolution.  

   Please contact igifford@earth.miami.edu for any queries. {"references": ["Andres, M., 2016. On the recent destabilization of the Gulf Stream path downstream of Cape Hatteras. Geophysical Research Letters, 43(18), 9836-9842.", "D'Errico, J., 2023. Consolidator (https://www.mathworks.com/matlabcentral/fileexchange/ 8354-consolidator), MATLAB Central File Exchange. Retrieved June 17, 2023.", "Gifford, Ian. H., 2023. The Synchronicity of the Gulf Stream Free Jet and the Wind Induced Cyclonic Vorticity Pool. MS Thesis, University of Massachusetts Dartmouth. 75pp.", "Gifford, Ian, H., Avijit Gangopadhyay, Magdalena Andres, Glen Gawarkiewicz, Hilde Oliver, Adrienne Silver, 2023. Wind Stress, Wind Stress Curl, and Upwelling Velocities in the Northwest Atlantic (80-45W, 30-45N) during 1980-2019, https://zenodo.org/record/8200832.", "Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H. and Miyaoka, K., 2015. The JRA-55 reanalysis: General specifications and basic characteristics.\u202fJournal of the Meteorological Society of Japan. Ser. II,\u202f93(1), pp.5-48. Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H. and Miyaoka, K., 2015. The JRA-55 reanalysis: General specifications and basic characteristics.\u202fJournal of the Meteorological Society of Japan. Ser. II,\u202f93(1), pp.5-48."]} 

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4. Seasonal and Annual Changes of the Regional Tropical Belt in GPS-RO Measurements and Reanalysis Datasets

   https://doi.org/10.1175/JCLI-D-19-0671.1  

   Luan, Lan ; Staten, Paul W. ; Ao, Chi O. ; Fu, Qiang ( May 2020 , Journal of Climate)

   The width of the tropical belt has been analyzed with a variety of metrics, often based on zonal-mean data from reanalyses. However, constraining the global and regional tropical width requires both a global spatial-resolving observational dataset and an appropriate metric to take advantage of such data. The tropical tropopause break is arguably such a metric. This study aims to evaluate the performance of different reanalyses and metrics with a focus on depicting regional tropical belt width. We choose four distinct tropopause-break metrics derived from global positioning system radio occultation (GPS-RO) satellite data and four modern reanalyses (ERA-Interim, MERRA-2, JRA-55, and CFSR). We show that reanalyses generally reproduce the regional tropical tropopause break to within 10° of that in GPS-RO data—but that the tropical width is somewhat sensitive (within 4°) to how data are averaged zonally, moderately sensitive (within 10°) to the dataset resolution, and more sensitive (20° over the Northern Hemisphere Atlantic Ocean during June–August) to the choice of metric. Reanalyses capture the poleward displacement of the tropical tropopause break over land and equatorward displacement over ocean during summertime, and the reverse during the wintertime. Reanalysis-based tropopause breaks are also generally well correlated with those from GPS-RO, although CFSR reproduces 14-yr trends much more closely than others (including ERA-Interim). However, it is hard to say which dataset is the best match of GPS-RO. We further find that the tropical tropopause break is representative of the subtropical jet latitude and the Northern Hemisphere edge of the Hadley circulation in terms of year-to-year variations.

    

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5. East Asian Rainbands and Associated Circulation over the Tibetan Plateau Region

   https://doi.org/10.1175/JCLI-D-21-0569.1  

   Liu, Jiabin ; Fung, Inez Y. ; Chiang, John C. H. ( June 2022 , Journal of Climate)

   Rainbands that migrate northward from spring to summer are persistent features of the East Asian summer monsoon. This study employs a machine learning algorithm to identify individual East Asian rainbands from May to August in the 6-hourly ERA-Interim reanalysis product and captures rainband events during these months for the period 1979–2018. The median duration of rainband events at any location in East Asia is 12 h, and the centroids of these rainbands move northward continuously from approximately 28°N in late May to approximately 33°N in July, instead of making jumps between quasi-stationary periods. Whereas the length and overall area of the rainbands grow monotonically from May to June, the intensity of the rainfall within the rainband dips slightly in early June before it peaks in late June. We find that extratropical northerly winds on all pressure levels over East China are the most important anomalous flow accompanying the rainband events. The anomalous northerlies augment climatological background northerlies in bringing low moist static energy air and thus generate the front associated with the rainband. Persistent lower-tropospheric southerly winds bring in moisture that feeds the rainband and are enhanced a few days prior to rainband events, but they are not directly tied to the actual rainband formation. The background northerlies could originate as part of the Rossby waves resulting from the jet stream interaction with the Tibetan Plateau. The ageostrophic circulation in the jet entrance region peaks in May and weakens in June and July and does not prove to be critical to the formation of the rainbands.

    

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