Satellite measures of vegetation greenness, together with animal stocking data and key climatic factors, reveal
interannual precipitation variability to be a significant constraint on global pasture productivity.
Importantly, the changes in cereal yield projected for the 2020s and 2080s are driven by GHG - induced climate change and likely do not fully capture
interannual precipitation variability which can result in large yield reductions during dry periods, as the IPCC (Christensen et al., 2007) states: ``... there is less confidence in the ability of the AOGCMs (atmosphere - ocean general circulation models) to generate interannual variability in the SSTs (sea surface temperatures) of the type known to affect African rainfall, as evidenced by the fact that very few AOGCMs produce droughts comparable in magnitude to the Sahel droughts of the 1970s and 1980s.»
Not exact matches
The ENSO phenomenon is one of the key factors that influence the
interannual variability of
precipitation over Southern South America.
Karl et al. [1995] examined
precipitation records over the 20th century and showed that the high - frequency (up to
interannual)
variability has increased.
The large
interannual to decadal hydroclimatic
variability in winter
precipitation is highly influenced by sea surface temperature (SST) anomalies in the tropical Pacific Ocean and associated changes in large - scale atmospheric circulation patterns [16].
Most model results project increased
interannual variability in season - averaged Asian monsoon
precipitation associated with an increase in its long - term mean value (e.g., Hu et al., 2000b; Räisänen, 2002; Meehl and Arblaster, 2003).
Links between
interannual variability of extreme
precipitation and temperatures offer possible observational constraints, especially since the underlying physical mechanisms are relatively well understood (e.g., O'Gorman and Schneider, 2009).
The statistics would be more robust with seasonal temperatures than with
precipitation for sure because
precipitation has a lot more
interannual variability.
In multi-year ensemble simulations driven by reanalyses of atmospheric observations, Vidale et al. (2003) show that RCMs have skill in reproducing
interannual variability in
precipitation and surface air temperature.
IPCC projections do not show obvious threshold behavior this century (12), but they do agree that sulfate aerosols would dampen the strength of ISM
precipitation, whereas increased greenhouse gases increase the
interannual variability of daily
precipitation (69).
Quan, M. P. Hoerling, A. Hoell, P. Peterson and W. M. Thiaw (May 2017): Climatology and
Interannual Variability of Boreal Spring Wet Season
Precipitation in the Eastern Horn of Africa and Implications for its Recent Decline.
9.3.1 Global Mean Response 9.3.1.1 1 % / yr CO2 increase (CMIP2) experiments 9.3.1.2 Projections of future climate from forcing scenario experiments (IS92a) 9.3.1.3 Marker scenario experiments (SRES) 9.3.2 Patterns of Future Climate Change 9.3.2.1 Summary 9.3.3 Range of Temperature Response to SRES Emission Scenarios 9.3.3.1 Implications for temperature of stabilisation of greenhouse gases 9.3.4 Factors that Contribute to the Response 9.3.4.1 Climate sensitivity 9.3.4.2 The role of climate sensitivity and ocean heat uptake 9.3.4.3 Thermohaline circulation changes 9.3.4.4 Time - scales of response 9.3.5 Changes in
Variability 9.3.5.1 Intra-seasonal variability 9.3.5.2 Interannual variability 9.3.5.3 Decadal and longer time - scale variability 9.3.5.4 Summary 9.3.6 Changes of Extreme Events 9.3.6.1 Temperature 9.3.6.2 Precipitation and convection 9.3.6.3 Extra-tropical storms 9.3.6.4 Tropical cyclones 9.3.6.5 Commentary on changes in extremes of weather and climate 9.3.6.6
Variability 9.3.5.1 Intra-seasonal
variability 9.3.5.2 Interannual variability 9.3.5.3 Decadal and longer time - scale variability 9.3.5.4 Summary 9.3.6 Changes of Extreme Events 9.3.6.1 Temperature 9.3.6.2 Precipitation and convection 9.3.6.3 Extra-tropical storms 9.3.6.4 Tropical cyclones 9.3.6.5 Commentary on changes in extremes of weather and climate 9.3.6.6
variability 9.3.5.2
Interannual variability 9.3.5.3 Decadal and longer time - scale variability 9.3.5.4 Summary 9.3.6 Changes of Extreme Events 9.3.6.1 Temperature 9.3.6.2 Precipitation and convection 9.3.6.3 Extra-tropical storms 9.3.6.4 Tropical cyclones 9.3.6.5 Commentary on changes in extremes of weather and climate 9.3.6.6
variability 9.3.5.3 Decadal and longer time - scale
variability 9.3.5.4 Summary 9.3.6 Changes of Extreme Events 9.3.6.1 Temperature 9.3.6.2 Precipitation and convection 9.3.6.3 Extra-tropical storms 9.3.6.4 Tropical cyclones 9.3.6.5 Commentary on changes in extremes of weather and climate 9.3.6.6
variability 9.3.5.4 Summary 9.3.6 Changes of Extreme Events 9.3.6.1 Temperature 9.3.6.2
Precipitation and convection 9.3.6.3 Extra-tropical storms 9.3.6.4 Tropical cyclones 9.3.6.5 Commentary on changes in extremes of weather and climate 9.3.6.6 Conclusions