Verification of moist surface variables over northern Australia in a high-resolution reanalysis (BARRA)
Peter T. May
A D , Blair Trewin B , Chun-Hsu Su B and Bertram Ostendorf C
A School of Earth Atmosphere and Environment, Monash University, Clayton, Australia.
B Bureau of Meteorology, Melbourne, Australia.
C University of Adelaide, Adelaide, Australia.
D Corresponding author. Email: peter.may@monash.edu
Journal of Southern Hemisphere Earth Systems Science 71(2) 194-202 https://doi.org/10.1071/ES21007
Submitted: 13 April 2021 Accepted: 6 August 2021 Published: 20 September 2021
Journal Compilation © BoM 2021 Open Access CC BY-NC-ND
Abstract
Reanalyses are important tools for understanding past weather and climate variability, but detailed verification of near surface humidity variables have not been published. This is particularly concerning in tropical regions where humid conditions impact meteorology and human activities. In this study, we used screen level temperature and humidity data from a high-resolution atmospheric regional reanalysis, the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA), validated against automatic weather stations (AWS) data for 32 sites across northern Australia. Overall, the BARRA data was reliable, with the time series from the AWS and BARRA being very highly correlated, but there were some seasonal and diurnally varying biases. The variability of the differences also changed from location to location and as a function of time of day and season, but much less than the biases. This variability was less than the ‘weather signal’ as evidenced by the high correlations. In particular, the amplitude of the diurnal cycle was overestimated, particularly in the dry (winter) season. In general, the differences in temperature were larger than those of the dew point temperature, and the wet bulb temperature had the least uncertainty. Overall, this study contributes to a better understanding of the effectiveness of reanalyses for examining the impact of moist variables on tropical climate variability.
Keywords: BARRA, BARRA-R, high-resolution reanalysis, humidity, northern Australia, verification, wet bulb temperature.
References
Betts, A. K., Köhler, M., and Zhang, Y. (2008). Comparison of river basin hydrometeorology in ERA-Interim and ERA-40 with observations. ECMWF Tech. Memo. 568, 18 pp.Bock, O., Keil, C., Richard, E., Flamant, C., and Boen, M.-N. (2005). Validation of precipitable water from ECMWF model analyses with GPS and radiosonde data during the MAP SOP. Quart. J. Roy. Meteor. Soc. 131, 3013–3036.
| Validation of precipitable water from ECMWF model analyses with GPS and radiosonde data during the MAP SOP.Crossref | GoogleScholarGoogle Scholar |
Bosilovich, M. G., Chen, J., Robertson, F. R., and Adler, R. F. (2008). Evaluation of global precipitation in reanalysis. J. Appl. Meteor. Climatol. 47, 2279–2299.
| Evaluation of global precipitation in reanalysis.Crossref | GoogleScholarGoogle Scholar |
Buck, A. (1981). New equations for computing vapor pressure and enhancement factor. J. Appl. Meteor 20, 1527–1552.
| New equations for computing vapor pressure and enhancement factor.Crossref | GoogleScholarGoogle Scholar |
Bush, M., Allen, T., Bain, C., Boutle, I., Edwards, J., Finnenkoetter, A., Franklin, C., Hanley, K., Lean, H., Lock, A., Manners, J., Mittermaier, M., Morcrette, C., North, R., Petch, J., Short, C., Vosper, S., Walters, D., Webster, S., Weeks, M., Wilkinson, J., Wood, N., and Zerroukat, M. (2020). The first Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL1. Geosci. Model Dev. 13, 1999–2029.
| The first Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL1.Crossref | GoogleScholarGoogle Scholar |
Decker, M., Brunke, M. A., Wang, Z., Sakaguchi, K., Zeng, X., and Bosilovich, M. G. (2012). Evaluation of the reanalysis products from GSFC, NCEP and ECMWF using flux tower observations. J. Clim. 25, 1916–1944.
| Evaluation of the reanalysis products from GSFC, NCEP and ECMWF using flux tower observations.Crossref | GoogleScholarGoogle Scholar |
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart, F. (2011). The Era-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc. 137, 553–597.
| The Era-Interim reanalysis: Configuration and performance of the data assimilation system.Crossref | GoogleScholarGoogle Scholar |
Jakobson, E., Vihma, T., Palo, T., Jakobson, L., Keernik, H., and Jaagus, J. (2012). Validation of atmospheric reanalyses over the central Arctic Ocean. Geophys. Res. Lett. 39, L10802.
| Validation of atmospheric reanalyses over the central Arctic Ocean.Crossref | GoogleScholarGoogle Scholar |
Jones, D. A., Wang, W., and Fawcett, R. (2009). High-quality spatial climate data-sets for Australia. Aust. Meteorol. Oceanogr. J. 58, 233–248.
| High-quality spatial climate data-sets for Australia.Crossref | GoogleScholarGoogle Scholar |
Keenan, T. D., and Carbone, R. E. (1992). A preliminary morphology of precipitation systems in tropical Northern Australia. Quart. J. Roy. Meteor. Soc. 118, 283–326.
| A preliminary morphology of precipitation systems in tropical Northern Australia.Crossref | GoogleScholarGoogle Scholar |
Lucas, C. (2010). A High-quality Historical Humidity Database for Australia, CAWCR Research Report 24, Bureau of Meteorology, ISBN 9781921605864 (pdf)
May, P. T. (1999). Thermodynamic and vertical velocity structure of two gust fronts observed with a wind profiler/RASS during MCTEX. Mon. Wea. Rev. 127, 1796–1807.
| Thermodynamic and vertical velocity structure of two gust fronts observed with a wind profiler/RASS during MCTEX.Crossref | GoogleScholarGoogle Scholar |
May, P. T., Protat, A., and Long, C. (2012). The diurnal cycle of the boundary layer, convection, clouds, and surface radiation in a coastal monsoon environment (Darwin Australia). J. Clim. 25, 5309–5326.
| The diurnal cycle of the boundary layer, convection, clouds, and surface radiation in a coastal monsoon environment (Darwin Australia).Crossref | GoogleScholarGoogle Scholar |
Stull, R. (2011). Wet-bulb temperature from relative humidity and air temperature. J. Appl. Meteor. Climatol. 50, 2265–22690.
| Wet-bulb temperature from relative humidity and air temperature.Crossref | GoogleScholarGoogle Scholar |
Su, C.-H., Eizenberg, N., Steinle, P., Jakob, D., Fox-Hughes, P., White, C. J., Rennie, S., Franklin, C., Dharssi, I., and Zhu, H. (2019). BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia. Geosci. Model Dev. 12, 2049–2068.
| BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia.Crossref | GoogleScholarGoogle Scholar |
Szczypta, C., Calvet, J.-C., Albergel, C., Balsamo, G., Boussetta, S., Carrer, D., Lafont, S., and Meurey, C. (2011). Verification of the new ECMWF ERA-Interim reanalysis over France. Hydrol. Earth Syst. Sci. 15, 647–666.
| Verification of the new ECMWF ERA-Interim reanalysis over France.Crossref | GoogleScholarGoogle Scholar |
Trewin, B. (2005). A notable frost hollow at Coonabarabran, New South Wales. Aust. Met. Mag. 54, 15–21.
Walters, D., Boutle, I., Brooks, M., Melvin, T., Stratton, R., Vosper, S., Wells, H., Williams, K., Wood, N., Allen, T., Bushell, A., Copsey, D., Earnshaw, P., Edwards, J., Gross, M., Hardiman, S., Harris, C., Heming, J., Klingaman, N., Levine, R., Manners, J., Martin, G., Milton, S., Mittermaier, M., Morcrette, C., Riddick, T., Roberts, M., Sanchez, C., Selwood, P., Stirling, A., Smith, C., Suri, D., Tennant, W., Vidale, P. L., Wilkinson, J., Willett, M., Woolnough, S., and Xavier, P. (2017). The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geosci. Model Dev. 10, 1487–1520.
| The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations.Crossref | GoogleScholarGoogle Scholar |
