We keep forgetting whether climate change is bad because it is bringing more rain or less rain. Or both, sometimes in the same place. So in our “IPCC AR6: Global trends in precipitation, unspun edition” let’s turn to Section 18.104.22.168.4 to clear things up. As is our custom we replace lists of references with (---) and occasionally spell out short forms for clarity, but otherwise this is the AR6 verbatim, not as paraphrased by journalists, politicians or Lancet editors. “In situ precipitation records over land extend back for centuries in a few locations, and to the early to mid-20th century quasi-globally. Datasets differ in their input data, completeness of records, period covered, and the gridding procedures which, given spatial clustering and the small spatial scales of precipitation, results in differences in global and regional estimates of precipitation changes (---). The spatial variability of observed long-term trends (1901–2019) based on GPCC V2020 and CRU TS 4.04 (Figure 2.15a,b) indicates significant increases in precipitation mainly over eastern North America, northern Eurasia, southern South America and northwestern Australia. Decreases are strongest across tropical western and equatorial Africa and southern Asia. The temporal evolution of global annual land precipitation anomalies exhibits little consistency between GPCC V2020, CRU TS 4.04 and GHCNv4 datasets, especially prior to 1950, that is associated with limitations in data coverage (---).”
Got it? If not, here’s some more analysis to unclarify things:
“These disagreements between datasets prior to the 1950s result in differences in trend estimates over global land (Table 2.6). A qualitative consistency in decadal and interdecadal variations between the products is only observed since the 1950s, with primarily positive land precipitation anomalies during the 1950s, 1970s and after the 2000s (Figure 2.15c).
Several satellite-based precipitation datasets improve the representation of the spatio-temporal changes since the late 20th century. Some of these are based exclusively on satellite data (---), with others being combinations of in situ observations, reanalyses and satellite retrievals (---). These can be affected by systematic and random uncertainties due to inhomogeneities in the satellite-derived precipitation and station data and the uncertainties of blending algorithms (---). The spatial coverage of these products is near-global, with available estimations formally covering 60°S–60°N with decreasing quality from low to high latitudes, depending on the sensors and algorithms used (---). A detailed description of the most relevant satellite products is provided in section 10.2.1.1.
Recent trends (1980–2019) for GPCC V2020, CRU TS 4.04 and GPCP V2.3 show significant increases in land precipitation over tropical Africa, the eastern portions of Europe and North America, central Asia and the Maritime Continent (Figure 2.14, d, e and f). Significant decreases are observed over central South America, western North America, northern Africa and the Middle East. A detailed assessment of the recent regional precipitation trends using the same datasets can be found in the Atlas. Global trends for 1980–2019 show a general increase in annual precipitation over land, which is particularly marked for CRU TS 4.04 and GHCNv4 (Table 2.6). These changes have been accompanied by a strengthening of precipitation seasonality over tropical land areas, although with broad spread between different satellite-based (---) and in situ gridded datasets (---).
In summary, globally averaged land precipitation has likely increased since the middle of the 20th century (medium confidence), with low confidence in trends prior to 1950. A faster increase in global land precipitation was observed since the 1980s (medium confidence), with large interannual variability and regional heterogeneity. Over the global ocean there is low confidence in the estimates of precipitation trends, linked to uncertainties in satellite retrievals, merging procedures and limited in situ observations.”