Papers on precipitation and global warming
Posted by Ari Jokimäki on March 11, 2011
This is a list of papers on precipitation changes with global warming. Both observational and model studies are included and there’s own section for regional and local studies where papers are just listed briefly without abstracts. Relatively small number of papers on the list arises from the emphasis on the precipitation papers only. Precipitation is included among other parameters to many papers analysing climate changes in general, but those papers are not included here. So far there has been not much effort to search regional and local papers, but only those were included that were found while searching for global papers. The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative.
How Much Will Precipitation Increase With Global Warming? – Lambert et al. (2008) “The advent of meteorological satellites during the 1970s made possible the observation of the seasonally shifting patterns of global precipitation. It was not until recently, however, that the record could be considered long enough to investigate longer-term trends and the relationship between global precipitation and global warming. Using data from the Special Sensor Microwave Imager (SSM/I) instrument, Wentz et al.  reported that global mean precipitation increased at a rate of 7.4 ± 2.6% per °C between 1987 and 2006.” Lambert, F. H., A. R. Stine, N. Y. Krakauer, and J. C. H. Chiang (2008), Eos Trans. AGU, 89(21), doi:10.1029/2008EO210001. [full text]
Muted precipitation increase in global warming simulations: A surface evaporation perspective – Richter & Xie (2008) “Atmospheric moisture content is expected to rise in response to global warming, but climate models predict a much slower rate of precipitation increase. This muted response of the hydrological cycle is investigated from a surface evaporation perspective, using a multimodel ensemble of simulations under the A1B forcing scenario. A 90-year analysis of surface evaporation based on a standard bulk formula reveals that the following atmospheric changes act to slow down the increase in surface evaporation over ice-free oceans: surface relative humidity increases by 1.0%, surface stability, as measured by air-sea temperature difference, increases by 0.2 K, and surface wind speed decreases by 0.02 m/s. As a result of these changes, surface evaporation increases by only 2% per Kelvin of surface warming, rather than the 7%/K rate simulated for atmospheric moisture. The increased surface stability and relative humidity are robust across models. The former is nearly uniform over ice-free oceans while the latter features a subtropical peak on either side of the equator. While relative humidity changes are positive almost everywhere in a thin surface layer, changes aloft show positive trends in the deep tropics and negative ones in the subtropics. The surface-trapped structure suggests the following mechanism: owing to its thermal inertia, the ocean lags behind the atmospheric warming, and this retarding effect causes an increase in surface stability and relative humidity, analogously to advection fog. Our results call for observational efforts to monitor and detect changes in surface relative humidity and stability over the world ocean.” Richter, I., and S.-P. Xie (2008), J. Geophys. Res., 113, D24118, doi:10.1029/2008JD010561.
How Much More Rain Will Global Warming Bring? – Wentz et al. (2007) “Climate models and satellite observations both indicate that the total amount of water in the atmosphere will increase at a rate of 7% per kelvin of surface warming. However, the climate models predict that global precipitation will increase at a much slower rate of 1 to 3% per kelvin. A recent analysis of satellite observations does not support this prediction of a muted response of precipitation to global warming. Rather, the observations suggest that precipitation and total atmospheric water have increased at about the same rate over the past two decades.” Frank J. Wentz, Lucrezia Ricciardulli, Kyle Hilburn and Carl Mears, Science 13 July 2007: Vol. 317 no. 5835 pp. 233-235, DOI: 10.1126/science.1140746. [full text]
On the tropical origin of uncertainties in the global land precipitation response to global warming – Douville et al. (2006) “Understanding the response of the global hydrological cycle to recent and future anthropogenic emissions of greenhouse gases and aerosols is a major challenge for the climate modelling community. Recent climate scenarios produced for the fourth assessment report of the Intergovernmental Panel on Climate Change are analysed here to explore the geographical origin of, and the possible reasons for, uncertainties in the hydrological model response to global warming. Using the twentieth century simulations and the SRES-A2 scenarios from eight different coupled ocean–atmosphere models, it is shown that the main uncertainties originate from the tropics, where even the sign of the zonal mean precipitation change remains uncertain over land. Given the large interannual fluctuations of tropical precipitation, it is then suggested that the El Niño Southern Ocillation (ENSO) variability can be used as a surrogate of climate change to better constrain the model reponse. While the simulated sensitivity of global land precipitation to global mean surface temperature indeed shows a remarkable similarity between the interannual and climate change timescales respectively, the model ability to capture the ENSO-precipitation relationship is not a major constraint on the global hydrological projections. Only the model that exhibits the highest precipitation sensitivity clearly appears as an outlier. Besides deficiencies in the simulation of the ENSO-tropical rainfall teleconnections, the study indicates that uncertainties in the twenty-first century evolution of these teleconnections represent an important contribution to the model spread, thus emphasizing the need for improving the simulation of the tropical Pacific variability to provide more reliable scenarios of the global hydrological cycle. It also suggests that validating the mean present-day climate is not sufficient to assess the reliability of climate projections, and that interannual variability is another suitable and possibly more useful candidate for constraining the model response. Finally, it is shown that uncertainties in precipitation change are, like precipitation itself, very unevenly distributed over the globe, the most vulnerable countries sometimes being those where the anticipated precipitation changes are the most uncertain.” H. Douville, D. Salas-Mélia and S. Tyteca, Climate Dynamics, Volume 26, Number 4, 367-385, DOI: 10.1007/s00382-005-0088-2. [full text]
Global observed changes in daily climate extremes of temperature and precipitation – Alexander et al. (2006) “A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed. By setting an exact formula for each index and using specially designed software, analyses done in different countries have been combined seamlessly. This has enabled the presentation of the most up-to-date and comprehensive global picture of trends in extreme temperature and precipitation indices using results from a number of workshops held in data-sparse regions and high-quality station data supplied by numerous scientists world wide. Seasonal and annual indices for the period 1951–2003 were gridded. Trends in the gridded fields were computed and tested for statistical significance. Results showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature. Over 70% of the global land area sampled showed a significant decrease in the annual occurrence of cold nights and a significant increase in the annual occurrence of warm nights. Some regions experienced a more than doubling of these indices. This implies a positive shift in the distribution of daily minimum temperature throughout the globe. Daily maximum temperature indices showed similar changes but with smaller magnitudes. Precipitation changes showed a widespread and significant increase, but the changes are much less spatially coherent compared with temperature change. Probability distributions of indices derived from approximately 200 temperature and 600 precipitation stations, with near-complete data for 1901–2003 and covering a very large region of the Northern Hemisphere midlatitudes (and parts of Australia for precipitation) were analyzed for the periods 1901–1950, 1951–1978 and 1979–2003. Results indicate a significant warming throughout the 20th century. Differences in temperature indices distributions are particularly pronounced between the most recent two periods and for those indices related to minimum temperature. An analysis of those indices for which seasonal time series are available shows that these changes occur for all seasons although they are generally least pronounced for September to November. Precipitation indices show a tendency toward wetter conditions throughout the 20th century.” Alexander, L. V., et al. (2006), J. Geophys. Res., 111, D05109, doi:10.1029/2005JD006290. [full text]
The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present) – Adler et al. (2003) “The Global Precipitation Climatology Project (GPCP) Version-2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5° latitude × 2.5° longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, and surface rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The dataset is extended back into the premicrowave era (before mid-1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the rain gauge analysis. The dataset archive also contains the individual input fields, a combined satellite estimate, and error estimates for each field. This monthly analysis is the foundation for the GPCP suite of products, including those at finer temporal resolution. The 23-yr GPCP climatology is characterized, along with time and space variations of precipitation.” Adler, Robert F., and Coauthors, 2003, J. Hydrometeor, 4, 1147–1167. [full text]
Simulated changes due to global warming in daily precipitation means and extremes and their interpretation using the gamma distribution – Watterson & Dix (2003) “The potential change in precipitation due to global warming is studied using five-member ensembles of climate simulations by the CSIRO Mark 2 atmosphere-ocean model for the period 1871–1990 and forward to 2100 under both the Special Report on Emission Scenarios (SRES) A2 (rapid CO2 increase) and B2 (moderate increase) forcing scenarios. The mean surface warming for the period 1961–1990 is 0.3 K. The warming from 1961–1990 to 2071–2100 is 3.5 K under A2, 29% more than for B2, and with a very similar spatial pattern. The daily precipitation (P) frequency distributions for January and July days in these periods are presented, focusing on the A2 case. The distributions for wet days at each point are approximated by the gamma distribution. The global mean P increase of around 6%, in both months, is related to a mean increase in the gamma’s scale parameter of 18%, offset by small decreases in the shape parameter and wet day frequency. However, local changes of opposite signs also occur, especially in the tropics. Ensemble averages of 30-year extreme daily precipitation for January and July, and other months, are generally greater for 2071–2100 than for 1961–1990, with an average increase of 14%. Extreme value theory based on the monthly gamma distributions provides a good match to these values. The theory is extended to the annual case. In general, the 1961–1990 extremes peak in the subtropical rainbands in the model, where increases of 10 to 30% are common. Larger relative increases occur in polar regions, and also over northern land in January.” Watterson, I. G., and M. R. Dix (2003), J. Geophys. Res., 108(D13), 4379, doi:10.1029/2002JD002928.
Changes in the Probability of Heavy Precipitation: Important Indicators of Climatic Change – Groisman et al. (1999) “A simple statistical model of daily precipitation based on the gamma distribution is applied to summer (JJA in Northern Hemisphere, DJF in Southern Hemisphere) data from eight countries: Canada, the United States, Mexico, the former Soviet Union, China, Australia, Norway, and Poland. These constitute more than 40% of the global land mass, and more than 80% of the extratropical land area. It is shown that the shape parameter of this distribution remains relatively stable, while the scale parameter is most variable spatially and temporally. This implies that the changes in mean monthly precipitation totals tend to have the most influence on the heavy precipitation rates in these countries. Observations show that in each country under consideration (except China), mean summer precipitation has increased by at least 5% in the past century. In the USA, Norway, and Australia the frequency of summer precipitation events has also increased, but there is little evidence of such increases in any of the countries considered during the past fifty years. A scenario is considered, whereby mean summer precipitation increases by 5% with no change in the number of days with precipitation or the shape parameter. When applied in the statistical model, the probability of daily precipitation exceeding 25.4 mm (1 inch) in northern countries (Canada, Norway, Russia, and Poland) or 50.8 mm (2 inches) in mid-latitude countries (the USA, Mexico, China, and Australia) increases by about 20% (nearly four times the increase in mean). The contribution of heavy rains (above these thresholds) to the total 5% increase of precipitation is disproportionally high (up to 50%), while heavy rain usually constitutes a significantly smaller fraction of the precipitation events and totals in extratropical regions (but up to 40% in the tropics, e.g., in southern Mexico). Scenarios with moderate changes in the number of days with precipitation coupled with changes in the scale parameter were also investigated and found to produce smaller increases in heavy rainfall but still support the above conclusions. These scenarios give changes in heavy rainfall which are comparable to those observed and are consistent with the greenhouse-gas-induced increases in heavy precipitation simulated by some climate models for the next century. In regions with adequate data coverage such as the eastern two-thirds of contiguous United States, Norway, eastern Australia, and the European part of the former USSR, the statistical model helps to explain the disproportionate high changes in heavy precipitation which have been observed.” Pavel Ya. Groisman, Thomas R. Karl, David R. Easterling, Richard W. Knight, Paul F. Jamason, Kevin J. Hennessy, Ramasamy Suppiah, Cher M. Page, Joanna Wibig and Krzysztof Fortuniak, et al., Climatic Change, Volume 42, Number 1, 243-283, DOI: 10.1023/A:1005432803188. [full text]
Precipitation sensitivity to global warming: Comparison of observations with HadCM2 simulations – Hulme et al. (1998) “Recent century‐long experiments performed with global climate models have simulated observed trends in global‐mean temperature quite successfully when both greenhouse gas and aerosol forcing has been included. The performance of these same experiments in simulating observed global‐scale changes in precipitation has not previously been examined. Here we use a gridded terrestrial precipitation dataset for the period 1900 to 1996 to examine the extent to which observed global and zonal‐mean precipitation sensitivities to global warming have been captured by a series of model simulations recently completed by the UK Hadley Centre. There are signs that the model has been able to reproduce at least some of the observed zonal‐mean variations in the precipitation sensitivity to warming. Questions remain both about the quality of the observed precipitation data and about the spatial scale at which anthropogenically‐forced global climate models can be expected to reproduce observed variations in precipitation.” Hulme, M., T. J. Osborn, and T. C. Johns (1998), Geophys. Res. Lett., 25(17), 3379–3382, doi:10.1029/98GL02562.
Global Precipitation: A 17-Year Monthly Analysis Based on Gauge Observations, Satellite Estimates, and Numerical Model Outputs – Xie & Arkin (1997) “Gridded fields (analyses) of global monthly precipitation have been constructed on a 2.5° latitude–longitude grid for the 17-yr period from 1979 to 1995 by merging several kinds of information sources with different characteristics, including gauge observations, estimates inferred from a variety of satellite observations, and the NCEP–NCAR reanalysis. This new dataset, which the authors have named the CPC Merged Analysis of Precipitation (CMAP), contains precipitation distributions with full global coverage and improved quality compared to the individual data sources. Examinations showed no discontinuity during the 17-yr period, despite the different data sources used for the different subperiods. Comparisons of the CMAP with the merged analysis of Huffman et al. revealed remarkable agreements over the global land areas and over tropical and subtropical oceanic areas, with differences observed over extratropical oceanic areas. The 17-yr CMAP dataset is used to investigate the annual and interannual variability in large-scale precipitation. The mean distribution and the annual cycle in the 17-yr dataset exhibit reasonable agreement with existing long-term means except over the eastern tropical Pacific. The interannual variability associated with the El Niño–Southern Oscillation phenomenon resembles that found in previous studies, but with substantial additional details, particularly over the oceans. With complete global coverage, extended period and improved quality, the 17-yr dataset of the CMAP provides very useful information for climate analysis, numerical model validation, hydrological research, and many other applications. Further work is under way to improve the quality, extend the temporal coverage, and to refine the resolution of the merged analysis.” Xie, Pingping, Phillip A. Arkin, 1997, Bull. Amer. Meteor. Soc., 78, 2539–2558. [full text]
Potential impacts of global warming on the frequency and magnitude of heavy precipitation – Fowler & Hennessy (1995) “It is now widely recognised that the most significant impacts of global warming are likely to be experienced through changes in the frequency of extreme events, including flooding. This paper reviews physical and empirical arguments which suggest that global warming may result in a more intense hydrological cycle, with an associated increase in the frequency and/or magnitude of heavy precipitation. Results derived from enhanced-greenhouse experiments using global climate models (GCMs) are shown to be consistent with these physical and empirical arguments. Detailed analysis of output from three GCMs indicates the possibility of substantial increases in the frequency and magnitude of extreme daily precipitation, with amplification of the effect as the return period increases. Moreover, return period analyses for locations in Australia, Europe, India, China and the USA indicate that the results are global in scope. Subsequent discussion of the limitations of GCMs for this sort of analysis highlights the need for caution when interpreting the precipitation results presented here. However, the consistency between physically-based expectations, empirical observations, and GCM results is considered sufficient for the GCM results to be taken seriously, at least in a qualitative sense, especially considering that the alternative seems to be reliance by planners on the fundamentally flawed concept of a stationary climate.” A. M. Fowler and K. J. Hennessy, Natural Hazards, Volume 11, Number 3, 283-303, DOI: 10.1007/BF00613411.
Regional and local studies
- South Africa: Fauchereau et al. (2003) [abstract]
- China: Gong & Wang (2000) [abstract, full text]
- Japan: Kimoto et al. (2005) [abstract, full text]
- Mongolia: Sato et al. (2007) [abstract, full text]
Australia and Oceania
North-America Kunkel et al. (2010) [abstract]
- Brazil: Dufek & Ambrizzi (2008) [abstract]