Modification signs in extreme weather events may be directly related to
alterations in the thermodynamic panorama of the atmosphere that need to be
better understood. This study aimed to make a first interconnection between
climate extremes and thermodynamic patterns in the city of Rio de Janeiro. Maximum and minimum air temperature and
precipitation extreme indices from
two surface meteorological stations (ABOV and STCZ) and instability indices
based on temperature and humidity from radiosonde observations (SBGL) were
employed to investigate changes in the periods 1964-1980 (P1), 1981-2000
(P2), and 2001-2020 (P3). Statistical tests were
adopted to determine the significance and magnitude of trends. The
frequency of warm (cold) days and warm
(cold) nights are increasing (decreasing) in the city. Cold (Warm) extremes
are changing with greater magnitude in ABOV (STCZ) than in STCZ (ABOV). In
ABOV, there is a significant increase of +84 mm/decade in the rainfall
volume associated with severe precipitation (above the 95th percentile) and most extreme precipitation indices show an increase in
frequency and intensity. In STCZ, there is a decrease in extreme
precipitation until the 1990s, and from there, an increase, showing a wetter
climate in the most recent years. It is
also verified in SBGL that there is a statistically significant increase (decrease) in air temperature of +0.1°C/decade (-0.2°C/decade) and relative humidity of +1.2%/decade (-3%/decade) at the low and middle (high)
troposphere. There is a visible rising trend in most of the evaluated
instability indices over the last few decades. The increasing trends of some
extreme precipitation indices are probably allied to the precipitable water
increasing trend of +1.2 mm/decade.
References
[1]
Allan, R., Barlow, M., Byrne, M. P., Cherchi, A. et al. (2020). Advances in Understanding Large-Scale Responses of the Water Cycle to Climate Change. Annals of the New York Academy of Sciences, 1472, 49-75. https://doi.org/10.1111/nyas.14337
[2]
Alvares, C. A., Stape, J. L., Sentelhas, P. C., Gonçalves, J. L. M., & Sparovek, G. (2014). Köppen’s Climate Classification Map for Brazil. Meteorologische Zeitschrift, 22, 711-728. https://doi.org/10.1127/0941-2948/2013/0507
[3]
Barata, M. M. L., Bader, D. A., Dereczynski, C. P., Regoto, P., & Rosenzweig, C. (2020). Use of Climate Change Projections for Resilience Planning in Rio de Janeiro, Brazil. Frontiers in Sustainable Cities, 2, Article No. 28. https://doi.org/10.3389/frsc.2020.00028
[4]
Blanchard, D. O. (1998). Mesoscale Convective Patterns of the Southern High Plains. Bulletin of the American Meteorological Society, 71, 994-1005. https://doi.org/10.1175/1520-0477(1990)071<0994:MCPOTS>2.0.CO;2
[5]
Boers, N., Bookhagen, B., Marwan, N., & Kurths, J. (2015). Spatiotemporal Characteristics and Synchronization of Extreme Rainfall in South America with Focus on the Andes Mountain Range. Climate Dynamics, 46, 601-617. https://doi.org/10.1007/s00382-015-2601-6
[6]
Bombardi, R. J., Carvalho, L. M. V., Jones, C., & Reboita, M. S. (2014). Precipitation over Eastern South America and the South Atlantic Surface Temperature during Neutral ENSO Periods. Climate Dynamics, 42, 1553-1568. https://doi.org/10.1007/s00382-013-1832-7
[7]
Bonnet, S. M., Dereczynski, C. P., & Nunes, A. (2018). Synoptic and Climatological Characterization of Post-Frontal Rainfall Events in Rio de Janeiro. Revista Brasileira de Meteorologia, 33, 547-557. https://doi.org/10.1590/0102-7786333013
[8]
Brooks, H. E., Anderson, A. R., Riemann, K., Ebbers, I., & Flachs, H. (2007). Climatological Aspects of Convective Parameters from the NCAR/NCEP Reanalysis. Atmospheric Research, 83, 294-305. https://doi.org/10.1016/j.atmosres.2005.08.005
[9]
Carvalho, L. M. V., Jones, C., & Liebmann, B. (2004). The South Atlantic Convergence Zone: Intensity, Form, Persistence, and Relationships with Intraseasonal to Interannual Activity and Extreme Rainfall. Journal of Climate, 17, 88-108. https://doi.org/10.1175/1520-0442(2004)017<0088:TSACZI>2.0.CO;2
[10]
Chung, E.-S., Soden, B., Sohn, B. J., & Shi, L. (2014). Upper-Tropospheric Moistening in Response to Anthropogenic Warming. Proceedings of the National Academy of Sciences of the United States of America, 111, 11636-11641. https://doi.org/10.1073/pnas.1409659111
[11]
Costa, A. J. S. T., Conceição, R. S., & Amante, F. O. (2018). The Floods and Urban Growth of Rio de Janeiro City: Studies toward an Cartography of Urban Floods. Geo UERJ, 32, e25685. https://doi.org/10.12957/geouerj.2018.25685
[12]
Costa, R. L., Baptista, G. M. M., Gomes, H. B., Silva, F. D. S. et al. (2020). Analysis of Climate Extremes Indices over Northeast Brazil from 1961 to 2014. Weather and Climate Extremes, 28, Article ID: 100254. https://doi.org/10.1016/j.wace.2020.100254
[13]
Dereczynski, C., Chou, S. C., Lyra, A., Sondermann, M. et al. (2020). Downscaling of Climate Extremes over South America—Part I: Model Evaluation in the Reference Climate. Weather and Climate Extremes, 29, Article ID: 100273. https://doi.org/10.1016/j.wace.2020.100273
[14]
Dereczynski, C., Luiz-Silva, W., & Marengo, J. (2013). Detection and Projections of Climate Change in Rio de Janeiro, Brazil. American Journal of Climate Change, 2, 25-33. https://doi.org/10.4236/ajcc.2013.21003
[15]
Derubertis, D. (2006). Recent Trends in Four Common Stability Indices Derived from US Radiosonde Observations. Journal of Climate, 19, 309-323. https://doi.org/10.1175/JCLI3626.1
[16]
Doswell III, C. A. (2001). Severe Convective Storms, Meteorological Monograph. American Meteorological Society. https://doi.org/10.1007/978-1-935704-06-5
[17]
Doswell III, C. A., & Schultz, D. M. (2006). On the Use of Indices and Parameters in Forecasting. Electronic Journal of Severe Storms Meteorology, 1, 1-22. https://doi.org/10.55599/ejssm.v1i3.4
[18]
Duarte, B. M., França, J. R. A., & Justo, L. A. J. (2018). The Use of CloudSat Data to Characterize the Microphysical Structure of Extreme Precipitation Events over South and Southeast of Brazil. Anuário do Instituto de Geociências—UFRJ, 41, 15-27. https://doi.org/10.11137/2018_1_15_27
[19]
Easterling, D. R., Meehl, G. A., Parmesan, C., Changnon, S. A. et al. (2000). Climate Extremes: Observations, Modeling and Impacts. Science, 289, 2068-2074. https://doi.org/10.1126/science.289.5487.2068
[20]
Emanuel, K. A. (1994). Atmospheric Convection. Oxford University Press.
[21]
Frich, P., Alexander, L. V., Della-Marta, P., Gleason, B. et al. (2002). Observed Coherent Changes in Climatic Extremes during the 2nd Half of the 20th Century. Climate Research, 19, 193-212. https://doi.org/10.3354/cr019193
[22]
Fujita, M., & Sato, T. (2017). Observed Behaviours of Precipitable Water Vapour and Precipitation Intensity in Response to Upper Air Profiles Estimated from Surface Air Temperature. Nature Scientific Reports, 7, Article No. 4233. https://doi.org/10.1038/s41598-017-04443-9
[23]
Geirinhas, J. L., Russo, A., Libonati, R., Sousa, P. M. et al. (2021). Recent Increasing Frequency of Compound Summer Drought and Heatwaves in Southeast Brazil. Environmental Research Letters, 16, Article ID: 034036. https://doi.org/10.1088/1748-9326/abe0eb
[24]
George, J. J. (1960). Weather Forecasting for Aeronautics. Academic Press.
[25]
Gulev, S. K., Thorne, P. W., Ahn, J., Dentener, F. J. et al. (2021). Changing State of the Climate System. In V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou (Eds.), Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 287-422). Cambridge University Press.
[26]
Held, I. M., & Soden, B. J. (2006). Robust Responses of the Hydrological Cycle to Global Warming. Journal of Climate, 19, 5686-5699. https://doi.org/10.1175/JCLI3990.1
[27]
Helsel, D. R., & Hirsch, R. M. (1992). Statistical Methods in Water Resources. Elsevier.
[28]
Henry, N. L. (2000). A Static Stability Index for Low-Topped Convection. Weather Forecast, 15, 246-254. https://doi.org/10.1175/1520-0434(2000)015<0246:ASSIFL>2.0.CO;2
[29]
IBGE (2021). Brazilian Institute of Geography and Statistics—Panorama Cidades e Estados. https://www.ibge.gov.br/cidades-e-estados/rj/rio-de-janeiro.html
[30]
IPCC (2021). Technical Summary. In V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou (Eds.), Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 33-144). Cambridge University Press.
[31]
Kendall, M. A., & Stuart, A. (1975). The Advanced Theory of Statistics. Charles Griffin.
[32]
Kunkel, K. E., Karl, T. R., Squires, M. F., Yin, X. et al. (2020). Precipitation Extremes: Trends and Relationships with Average Precipitation and Precipitable Water in the Contiguous United States. Journal of Applied Meteorology and Climatology, 59, 125-142. https://doi.org/10.1175/JAMC-D-19-0185.1
[33]
Kunz, M. (2007). The Skill of Convective Parameters and Indices to Predict Isolated and Severe Thunderstorms. Natural Hazards and Earth System Sciences, 7, 327-342. https://doi.org/10.5194/nhess-7-327-2007
[34]
La Rovere, E. L., & Silva de Sousa, D. (2016). Estratégia de adaptação às mudanças climáticas da cidade do Rio de Janeiro. Rio Prefeitura Meio Ambiente, Rio de Janeiro.
[35]
Leyba, I. M., Solman, S. A., & Saraceno, M. (2019). Trends in Sea Surface Temperature and Air-Sea Heat Fluxes over the South Atlantic Ocean. Climate Dynamics, 53, 4141-4153. https://doi.org/10.1007/s00382-019-04777-2
[36]
Lopez, P. (2007). Cloud and Precipitation Parameterizations in Modeling and Variational Data Assimilation: A Review. Journal of the Atmospheric Sciences, 64, 3766-3784. https://doi.org/10.1175/2006JAS2030.1
[37]
Luiz-Silva, W., & Dereczynski, C. P. (2014). Climatological Characterization and Observed Trends in Climatic Extremes in the State of Rio de Janeiro. Anuário do Instituto de Geociências—UFRJ, 37, 123-138. https://doi.org/10.11137/2014_2_123_138
[38]
Luiz-Silva, W., & Oscar-Júnior, A. C. (2022). Climate Extremes Related with Rainfall in the State of Rio de Janeiro, Brazil: A Review of Climatological Characteristics and Recorded Trends. Natural Hazards, 114, 713-732. https://doi.org/10.1007/s11069-022-05409-5
[39]
Luiz-Silva, W., Oscar-Júnior, A. C., Cavalcanti, I. F. A., & Treistman, F. (2021). An Overview of Precipitation Climatology in Brazil: Space-Time Variability of Frequency and Intensity Associated with Atmospheric Systems. Hydrological Sciences Journal, 66, 289-308. https://doi.org/10.1080/02626667.2020.1863969
[40]
Luiz-Silva, W., Xavier, L. N. R., Maceira, M. E. P., & Rotunno, O. C. (2019). Climatological and Hydrological Patterns and Verified Trends in Precipitation and Streamflow in the Basins of Brazilian Hydroelectric Plants. Theoretical and Applied Climatology, 137, 353-371. https://doi.org/10.1007/s00704-018-2600-8
[41]
Mann, H. B. (1945). Non-Parametric Tests against Trend. Econometrica, 13, 245-259. https://doi.org/10.2307/1907187
[42]
Marengo, J. A., Souza Jr., C. M., Thonicke, K., Burton, C. et al. (2018). Changes in Climate and Land Use over the Amazon Region: Current and Future Variability and Trends. Frontiers in Earth Science, 6, Article No. 228. https://doi.org/10.3389/feart.2018.00228
[43]
Mears, C. A., & Wentz, F. J. (2009). Construction of the Remote Sensing Systems V3.2 Atmospheric Temperature Records from the MSU and AMSU Microwave Sounders. Journal of Atmospheric and Oceanic Technology, 26, 1040-1056. https://doi.org/10.1175/2008JTECHA1176.1
[44]
Miller, R. C. (1972). Notes on Analysis and Severe Storm Forecasting Procedures of the Air Force Global Weather Center. Technical Report 200 (Rev), Air Weather Service (MAC) United States Air Force.
[45]
Miloshevich, L. M., Võmel, H., Whiteman, D. N., & Leblanc, T. (2009). Accuracy Assessment and Correction of Vaisala RS92 Radiosonde Water Vapor Measurements. Journal of Geophysical Research, 114, D11305. https://doi.org/10.1029/2008JD011565
[46]
Mitovski, T., Folkins, I., von Salzen, K., & Sigmond, M. (2010). Temperature, Relative Humidity, and Divergence Response to High Rainfall Events in the Tropics: Observations and Models. Journal of Climate, 23, 3613-3625. https://doi.org/10.1175/2010JCLI3436.1
[47]
Nascimento, E. L. (2005). Severe Storms Forecasting Utilizing Convective Parameters and Mesoscale Models: An Operational Strategy Adoptable in Brazil? Revista Brasileira de Meteorologia, 20, 121-140.
[48]
Nunes, K. R. A., Abelheira, M., Gomes, O. S., Martins, P., & Aguiar, I. S. (2020). Disaster Risk Assessment: The Experience of the City of Rio de Janeiro in Developing an Impact Scale for Meteorological-Related Disasters. Progress in Disaster Science, 5, Article ID: 100053. https://doi.org/10.1016/j.pdisas.2019.100053
[49]
O’Gorman, P. A. (2015). Precipitation Extremes under Climate Change. Current Climate Change Reports, 1, 49-59. https://doi.org/10.1007/s40641-015-0009-3
[50]
O’Gorman, P. A., & Schneider, T. (2009). The Physical Basis for Increases in Precipitation Extremes in Simulations of 21st-Century Climate Change. Proceedings of the National Academy of Sciences of the United States of America, 106, 14773-14777. https://doi.org/10.1073/pnas.0907610106
[51]
Pall, P., Allen, M. R., & Stone, D. A. (2007). Testing the Clausius-Clapeyron Constraint on Changes in Extreme Precipitation under CO2 Warming. Climate Dynamics, 28, 351-363. https://doi.org/10.1007/s00382-006-0180-2
[52]
Paltridge, G., Arking, A., & Pook, M. (2009). Trends in Middle- and Upper-Level Tropospheric Humidity from NCEP Reanalysis Data. Theoretical and Applied Climatology, 98, 351-359. https://doi.org/10.1007/s00704-009-0117-x
[53]
Peres, L. F., Lucena, A. J., Rotunno Filho, O. C., & França, J. R. A. (2018). The Urban Heat Island in Rio de Janeiro, Brazil, in the Last 30 Years Using Remote Sensing Data. The International Journal of Applied Earth Observation and Geoinformation, 64, 104-116. https://doi.org/10.1016/j.jag.2017.08.012
[54]
Poujol, B., Sobolowski, S. P., Mooney, P. A., & Berthou, S. (2020). A Physically Based Precipitation Separation Algorithm for Convection-Permitting Models over Complex Topography. Quarterly Journal of the Royal Meteorological Society, 146, 748-761. https://doi.org/10.1002/qj.3706
[55]
Randel, W. J., Polvani, L. P., Wu, F., Kinnison, D. E. et al. (2017). Troposphere-Stratosphere Temperature Trends Derived from Satellite Data Compared with Ensemble Simulations from WACCM. JGR Atmospheres, 122, 9651-9667. https://doi.org/10.1002/2017JD027158
[56]
Rasmussen, E. N., & Blanchard, D. O. (1998). A Baseline Climatology of Sounding-Derived Supercell and Tornado Forecast Parameters. Weather Forecast, 13, 1148-1164. https://doi.org/10.1175/1520-0434(1998)013<1148:ABCOSD>2.0.CO;2
[57]
Regoto, P., Dereczynski, C., Chou, S. C., & Bazzanela, A. C. (2021). Observed Changes in Air Temperature and Precipitation Extremes over Brazil. International Journal of Climatology, 41, 5125-5142. https://doi.org/10.1002/joc.7119
[58]
Sapucci, L. F., Machado, L. A. T., Silveira, R. B., Fisch, G., & Monico, J. F. G. (2005). Analysis of Relative Humidity Sensor Sat the WMO Radiosonde Intercomparison Experiment in Brazil. Journal of Atmospheric and Oceanic Technology, 22, 664-678. https://doi.org/10.1175/JTECH1754.1
[59]
Schumacher, C., & Houze Jr., R. A. (2003). Stratiform Rain in the Tropics as Seen by the TRMM Precipitation Radar. Journal of Climate, 16, 1739-1756. https://doi.org/10.1175/1520-0442(2003)016<1739:SRITTA>2.0.CO;2
[60]
Schumacher, R. S., & Peters, J. M. (2017). Near-Surface Thermodynamic Sensitivities in Simulated Extreme-Rain-Producing Mesoscale Convective Systems. Monthly Weather Review, 145, 2177-2200. https://doi.org/10.1175/MWR-D-16-0255.1
[61]
Seidel, D. J., Free, M., & Wang, J. (2005). Diurnal Cycle of Upper-Air Temperature Estimated from Radiosondes. Journal of Geophysical Research: Atmospheres, 110, D9. https://doi.org/10.1029/2004JD005526
[62]
Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall’s Tau. Journal of the American Statistical Association, 63, 1379-1389. https://doi.org/10.1080/01621459.1968.10480934
[63]
Shepherd, T. G. (2014). Atmospheric Circulation as a Source of Uncertainty in Climate Change Projections. Nature Geoscience, 7, 703-708. https://doi.org/10.1038/ngeo2253
[64]
Silva Dias, M. A. F. (1987). Sistemas de mesoescala e previsão de tempo a curto prazo. Revista Brasileira de Meteorologia, 2, 133-150.
[65]
Silva, F. P., Justi da Silva, M. G. A., Rotunno Filho, O. C., Pires, G. D. et al. (2019b). Synoptic Thermodynamic and Dynamic Patterns Associated with Quitandinha River Flooding Events in Petropolis, Rio de Janeiro (Brazil). Meteorology and Atmospheric Physics, 131, 845-862. https://doi.org/10.1007/s00703-018-0609-2
[66]
Silva, F. P., Rotunno Filho, O. C., Justi da Silva, M. G. A., Sampaio, R. J. et al. (2020). Observed and Estimated Atmospheric Thermodynamics Instability Using Radiosonde Observations over the City of Rio de Janeiro, Brazil. Meteorology and Atmospheric Physics, 132, 297-314. https://doi.org/10.1007/s00703-019-00688-3
[67]
Silva, F. P., Rotunno Filho, O. C., Sampaio, R. J., Dragaud, I. C. D. V. et al. (2019a). Evaluation of Atmospheric Thermodynamics and Dynamics during Heavy-Rainfall and No-Rainfall Events in the Metropolitan Area of Rio de Janeiro, Brazil. Meteorology and Atmospheric Physics, 131, 299-311. https://doi.org/10.1007/s00703-017-0570-5
[68]
Sneyers, R. (1990). On the Statistical Analysis of Series of Observations. World Meteorological Organization.
[69]
Soden, B. J., Jackson, D. L., Ramaswamy, V., Schwarzkopf, M. D., & Huang, X. (2005). The Radiative Signature of Upper Tropospheric Moistening. Science, 310, 841-844. https://doi.org/10.1126/science.1115602
[70]
Steiner, A. K., Ladstädter, F., Randel, W. J., Maycock, A. C. et al. (2020). Observed Temperature Changes in the Troposphere and Stratosphere from 1979 to 2018. Journal of Climate, 33, 8165-8194. https://doi.org/10.1175/JCLI-D-19-0998.1
[71]
Taszarek, M., Brooks, H. E., Czernecki, B., Szuster, P., & Fortuniak, K. (2018). Climatological Aspects of Convective Parameters over Europe: A Comparison of ERA-Interim and Sounding Data. Journal of Climate, 31, 4281-4308. https://doi.org/10.1175/JCLI-D-17-0596.1
[72]
Timmermann, A., An, S.-I., Kug, J.-S., Jin, F.-F. et al. (2018). El-Niño-Southern Oscillation Complexity. Nature, 559, 535-545. https://doi.org/10.1038/s41586-018-0252-6
[73]
Tremblay, A. (2005). The Stratiform and Convective Components of Surface Precipitation. Journal of the Atmospheric Sciences, 62, 1513-1528. https://doi.org/10.1175/JAS3411.1
[74]
Trenberth, K. E., Dai, A., Rasmussen, R. M., & Parsons, D. B. (2003). The Changing Character of Precipitation. Bulletin of the American Meteorological Society, 84, 1205-1217. https://doi.org/10.1175/BAMS-84-9-1205
[75]
Westra, S., Alexander, L. V., & Zwiers, F. W. (2013). Global Increasing Trends in Annual Maximum Daily Precipitation. Journal of Climate, 26, 3904-3918. https://doi.org/10.1175/JCLI-D-12-00502.1
[76]
Westra, S., Fowler, H. J., Evans, J. P., Alexander, L. V. et al. (2014). Future Changes to the Intensity and Frequency of Short-Duration Extreme Rainfall. Reviews of Geophysics, 52, 522-555. https://doi.org/10.1002/2014RG000464
[77]
Zandonadi, L., Acquaotta, F., Fratianni, S., & Zavattini, J. A. (2016). Changes in Precipitation Extremes in Brazil (Paraná River Basin). Theoretical and Applied Climatology, 123, 741-756. https://doi.org/10.1007/s00704-015-1391-4
[78]
Zhang, X., Feng, Y., & Chan, R. (2018). Introduction to RClimDex v1.9. Climate Research Division, Canada.
[79]
Zilli, M. T., Carvalho, L. M. V., & Lintner, B. R. (2019). The Poleward Shift of South Atlantic Convergence Zone in Recent Decades. Climate Dynamics, 52, 2545-2563. https://doi.org/10.1007/s00382-018-4277-1
[80]
Zilli, M. T., Carvalho, L. M. V., Liebmann, B., & Silva Dias, M. A. (2017). A Comprehensive Analysis of Trends in Extreme Precipitation over Southeastern Coast of Brazil. International Journal of Climatology, 37, 2269-2279. https://doi.org/10.1002/joc.4840
[81]
Zveryaev, I. I., & Chu, P.-S. (2003). Recent Climate Changes in Precipitable Water in the Global Tropics as Revealed in National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis. JGR Atmospheres, 108, D10. https://doi.org/10.1029/2002JD002476
