If we want to assess forecasts of floods, droughts and crop yields then we will need to know rainfall. We will also need to know temperature of course.
The forte of climate models is temperature. Rainfall is more problematic.
Before we get to model predictions about the future we need to review observations and the ability of models to reproduce them. Observations are also problematic – rainfall varies locally and over short durations. And historically we lacked effective observation systems in many locations and regions of the world, so data has to be pieced together and estimated from reanalysis.
Smith and his colleagues created a new rainfall dataset. Here is a comment from their 2012 paper:
Although many land regions have long precipitation records from gauges, there are spatial gaps in the sampling for undeveloped regions, areas with low populations, and over oceans. Since 1979 satellite data have been used to fill in those sampling gaps. Over longer periods gaps can only be filled using reconstructions or reanalyses..
Here are two views of the global precipitation data from a dataset which starts with the satellite era, that is, 1979 onwards – GPCP (Global Precipitation Climatology Project):
Figure 1
Figure 2
For historical data before satellites we only have rain gauge data. The GPCC dataset, explained in Becker et al 2013, shows the number of stations over time by region:
Figure 3- Click to expand
And the geographical distribution of rain gauge stations at different times:
Figure 4 – Click to expand
The IPCC compared the global trends over land from four different datasets over the last century and the last half-century:
Figure 5 – Click to expand
And the regional trends:
Figure 6 – Click to expand
The graphs for the annual change in rainfall, note the different scales for each region (as we would expect given the difference in average rainfall in different region):
Figure 7
We see that the decadal or half-decadal variation is much greater than any apparent long term trend. The trend data (as reviewed by the IPCC in figs 5 & 6) shows significant differences in the datasets but when we compare the time series it appears that the datasets match up better than indicated by the trend comparisons.
The data with the best historical coverage is 30ºN – 60ºN and the trend values for 1951-2000 (from different reconstructions) range from an annual increase of 1 to 1.5 mm/yr per decade (fig 6 / table 2.10 of IPCC report). This is against an absolute value of about 1000 mm/yr in this region (reading off the climatology in figure 2).
This is just me trying to put the trend data in perspective.
Models
Here is the IPCC AR5 chapter 9 on model comparisons to satellite-era rainfall observations. Top left is observations (basically the same dataset as figure 1 in this article over a slightly longer period with different colors) and bottom right is percentage error of model average with respect to observations:
Figure 8 – Click to expand
We can see that the average of all models has substantial errors on mean rainfall.
Articles in this Series
Impacts – II – GHG Emissions Projections: SRES and RCP
Impacts – III – Population in 2100
Impacts – IV – Temperature Projections and Probabilities
Impacts – V – Climate change is already causing worsening storms, floods and droughts
Impacts – VI – Sea Level Rise 1
Impacts – VII – Sea Level 2 – Uncertainty
Impacts – VIII – Sea level 3 – USA
Impacts – IX – Sea Level 4 – Sinking Megacities
Impacts – X – Sea Level Rise 5 – Bangladesh
References
IPCC AR5 Chapter 2
Improved Reconstruction of Global Precipitation since 1900, Smith, Arken, Ren & Shen, Journal of Atmospheric and Oceanic Technology (2012)
The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present), Adler et al, Journal of Hydrometeorology (2003)
A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present, A Becker, Earth Syst. Sci. Data (2013)
My two cents on relating extreme rainfall events to fossil fuel emissions.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2929159
Thanks SoD – I hadn’t seen the uncertainty as indicated by the variance of estimated trends. Maybe a typo in the take away statement?
“We see that the decadal or half-decadal variation is much greater than any apparent long term trend. “
->“We see that the centennial or half-centennial variation is much greater than any apparent long term trend. “
The effect of the rate of increase of precipitation on climate sensitivity is large. A high rate of increase of precipitation means a low climate sensitivity and conversely. Most, if not all, models with high climate sensitivity have a low rate of increase of precipitation with temperature. As we can see above, models don’t do precipitation well at all.
Yes. And this paper detailing the failings is revealing.
GCMs predict much more tropical precipitation than is observed and this explains the hot spot in the models that is (so far) not observed.
And this failing has gotten worse, not better from CMIP3 to CMIP5.
A double ITCZ? A single ITCZ is a major observable feature of the real world. How can anyone take GCM’s seriously? Mosher would say that they’re better than nothing, which is probably true. But they’re not much better than nothing.
“If we want to assess forecasts of floods, droughts…”
Again, I think it’s useful to point out what IPCC AR5 actually says about floods and droughts:
Chapter 2:
“In summary, there continues to be a lack of evidence and thus low confidence regarding the sign of trend in the magnitude and/or frequency of floods on a global scale.”
SPM:
“Increases in intensity and/or duration of drought since 1950: low confidence on a global scale, likely changes in some regions. Assessment of a human contribution to observed changes: low confidence.”
Paul,
I’ve highlighted this in Impacts – V – Climate change is already causing worsening storms, floods and droughts
Paul: One might add that significant numbers of people haven’t lived along “natural” rivers for almost a century. The risk of flooding that exists is mostly due to the choices man has made in modifying rivers. Compared with those modifications, climate change is likely a minor consideration.
SoD. Thank you for showing the systematic bias of models on rainfall. It is very unpleasant to know that these models are being used as guides when we shall calculate climate change for the next 100 years or more. When we also know that there are systematic biases when it comes to composition of clouds, cloud – aerosol interaction, ocean temperature gradient, and much more. We are asked to follow some leaders, and we know that they have wrong maps.
“Precipitation anomalies have been stronger and covered larger areas in some earlier centuries than during the twentieth century”, according to Fredrik Charpentier Ljungqvist,
Northern Hemisphere hydroclimate variability over the past twelve centuries
Fredrik Charpentier Ljungqvist, Paul J. Krusic, Hanna S. Sundqvist, Eduardo Zorita, Gudrun Brattström & David Frank. 2016.
Presentation: http://www.bolin.su.se/index.php/news/430-new-nature-article-northern-hemisphere-hydroclimate-variability-over-the-past-twelve-centuries
” According to a new study in Nature, the Northern Hemisphere has experienced considerably larger variations in precipitation during the past twelve centuries than in the twentieth century. Researchers from Sweden, Germany, and Switzerland have found that climate models overestimated the increase in wet and dry extremes as temperatures increased during the twentieth century. ”
“However, unlike the climate model simulations, the new precipitation reconstruction does not show an increase of wet and dry anomalies in the twentieth century compared to the natural variations of the past millennium. The precipitation reconstruction contains some uncertainties. Nevertheless the difference between the simulated and the reconstructed precipitation in the twentieth century is a robust feature and the reconstruction also agrees with meteorological measurements.” and “the new precipitation reconstruction suggests that it is much harder to predict precipitation changes than previously thought.”
One interesting finding was that the period between 1200 and 1400 was a wet period. Wet and cold.