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Precipitation variability in space and time has been a focus of research over the past decades. The largest body of literature was essentially focused on long-term changes in average climates and in climate extremes. Analyses of the changes in the inter-annual climate variability (the year-to-year variability), which represent an index of climatic risk, received instead very less attention, but it represents an important issue in order to quantitatively measure the socioeconomic impact of climate change impact over water resources. In order to depict a general characterization of the long-term climate variability for the Campania region, located in Southern Italy within the Mediterranean basin, an analysis of the precipitation coefficient of variation, assumed as an index of inter-annual climate variability, was performed over the period 1918–2015 and compared with the annual precipitation regime and the intra-annual precipitation variability of the same region. The Mann–Kendall and the modified Mann–Kendall tests were applied to detect the sign and significance of the temporal changes and Sen’s test was applied to quantify the temporal changes in inter-annual variability. The results illustrated a generalized condition (73% of total stations) of statistically significant increase of inter-annual variability distributed almost over the whole analyzed area, even though the detected change appeared rather moderate in magnitude. The relationship between annual precipitation, intra-annual precipitation variability, and inter-annual precipitation variability was not clearly identified for the studied region, likely because of the characteristics of climatic homogeneity for the area under investigation. However, the comparative analyzes clearly showed how, if the variations in the annual precipitation regime and in the intra-annual precipitation variability are poorly significant (respectively for 9% and 11% of total station), changes in inter-annual precipitation variability are strongly marked over the studied region.

Summer precipitation in the north fringe of East Asian Summer Monsoon (NFEASM) accounts for the majority of annual regional precipitation and plays an important role in regional climatology and agriculture development. Here we analyze variations in summer precipitation in the NFEASM over the past millennium using several simulations with Earth System Models and compare with two dendroclimatological hydroclimate reconstructions that partly cover the past millennium. Both reconstructed records show good agreement on past hydroclimate variations but do not show overly anomalous hydroclimate periods, except for clear drying trends in the second half of the twentieth century. The reconstructed decadal hydroclimate variations are not correlated with any of the simulations, and the simulations are not correlated among themselves either, which strongly suggests that the decadal variability is not linked to the external climate forcing. In addition, the superposed epoch analysis also does not identify a response of simulated precipitation to volcanic eruptions. Therefore, precipitation variability in this region over the past millennium seems to have been driven by internal climate processes. In the simulations, regional summer precipitation is positively and significantly correlated with sea-level-pressure (SLP) over the North Pacific and is negatively and significantly correlated with SLP in southwestern China at both interannual and decadal time scales. This agrees with the teleconnection patterns identified from meteorological reanalysis datasets, indicating that this dipole correlation pattern is robust. Therefore, the SLP difference between these two areas is used as an index to identify the atmosphere circulation pattern favorable to summer precipitation in the NFEASM. This SLP index shows spatial variable correlations with sea-surface-temperature (SST) in the North Pacific: there is a significant positive correlation in the northern North Pacific, while a significant negative correlation in the southern North Pacific. Although the underlying mechanisms for these correlations likely differ between two subareas, it appears that the atmosphere drives SST anomalies in the both subareas.

The inter-decadal variation of the positive relationship between the tropical Atlantic sea surface temperature (SST) and Korean precipitation during boreal summer season during 1900–2010 is examined. The 15-year moving correlation between the Tropical Atlantic SST (TAtlSST) index (SST anomalies from 30°S to 30°N and 60°W to 20°E) and Korean precipitation (precipitation anomalies from 35°–40°N to 120°–130°E) during June–July–August exhibits strong inter-decadal variation, which becomes positive at the 95% confidence level after the 1980s. Intensification of the linkage between the TAtlSST index and Korean precipitation after the 1980s is attributed to global warming via the increased background SST. The increase in the background SST over the Atlantic provides background conditions that enhance anomalous convective activity by anomalous Atlantic SST warming. Therefore, the overall atmospheric responses associated with the tropical Atlantic SST warming could intensify. The correlation between the TAtlSST index and Korean precipitation also exhibits strong inter-decadal variation within 1980–2010, which is over 0.8 during early 2000s, while it is relative low (i.e., around 0.6) during the early 1980s. The enhanced co-variability between the tropical and the mid-latitude Atlantic SST during the early 2000s indicates the intensification of TAtlSST-related Rossby wave source over the mid-latitude Atlantic, which excites stationary waves propagated from the Atlantic to the Korean peninsula across northern Europe and northeast Asia. This Rossby-wave train induces a cyclonic flow over the northern edge of the Korea, which intensifies southwesterly and results in precipitation over Korea. This observed decadal difference is well simulated by the stationary wave model experiments with a prescribed TAtlSST-related Rossby wave source over the mid-latitude Atlantic.

Previous studies have found that under global warming, El Niño/Southern Oscillation (ENSO)-related rainfall variability will become enhanced over the tropical central-eastern Pacific and weakened over the western Pacific. The climatological sea surface temperature (SST) warming pattern exhibits a warming center in the equatorial eastern Pacific in projections. How this pattern contributes to projected changes in ENSO-driven rainfall variability has not been fully addressed. Here, we use “time-slice” experiments to investigate the response of interannual variability in tropical Pacific rainfall in boreal winter to a warming background SST and associated physical mechanisms. A high-resolution Atmosphere General Circulation Model is driven by the detrended observational SST (1979–2003) plus a warming pattern from the coupled model under the A1B emission scenario (2075–2099). The results show that precipitation interannual variability over the tropical central-eastern Pacific will be enhanced more than the surrounding regions under warming, which is mostly contributed by a faster increase in rainfall amount during the El Niño year relative to non-El Niño years. Based on a moisture budget analysis, both the dynamic and thermodynamic components in the vertical advection of climatological specific humidity contribute to the enhancement of El Niño-induced precipitation anomalies in the tropical central-eastern Pacific where the dynamic effect is dominant. Moist static energy budget analysis further illustrates that vertical velocity is enhanced due to the increased transport of moist static energy from the lower troposphere into the middle-upper troposphere and the intensified warming effect of cloud longwave radiation caused by the increase of high cloud amount and altitude.

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According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe 1 – 4 . However, verifying this prediction using observations has remained a substantial challenge owing to large natural rainfall fluctuations at regional scales 3 , 4 . Here we show that deep learning successfully detects the emerging climate-change signals in daily precipitation fields during the observed record. We trained a convolutional neural network (CNN) 5 with daily precipitation fields and annual global mean surface air temperature data obtained from an ensemble of present-day and future climate-model simulations 6 . After applying the algorithm to the observational record, we found that the daily precipitation data represented an excellent predictor for the observed planetary warming, as they showed a clear deviation from natural variability since the mid-2010s. Furthermore, we analysed the deep-learning model with an explainable framework and observed that the precipitation variability of the weather timescale (period less than 10 days) over the tropical eastern Pacific and mid-latitude storm-track regions was most sensitive to anthropogenic warming. Our results highlight that, although the long-term shifts in annual mean precipitation remain indiscernible from the natural background variability, the impact of global warming on daily hydrological fluctuations has already emerged. Deep learning using a convolutional neural network trained with daily precipitation fields and annual global mean surface air temperature data demonstrates that anthropogenically induced climate change has a detectable effect on daily hydrological fluctuations.

How global precipitation might have changed on the interdecadal-to-multi-decadal time scales during the satellite (post-1979) era is examined by means of the satellite-based GPCP V2.3 monthly precipitation analysis. Comparisons with the results from CMIP6 and AMIP6 are further made in terms of global mean precipitation change and regional features of precipitation change, aiming to provide not only an improved understanding of the effects of major physical mechanisms on precipitation change, but also an assessment of the skills of current climate models and likely some clues for diagnosing possible limitations in observed precipitation. Long-term change/trend in global mean precipitation is generally weak in GPCP. Although the GPCP trend is statistically significant at the 90% confidence level over global land + ocean during 1979–2020, it is not significant over either global land or ocean separately. For the shorter, overlap period with the CMIP6 historical experiments (1979–2014), GPCP positive trends can’t reach the 90% confidence level, while significant and more intense precipitation trends appear in CMIP6 ensemble-means. However, a roughly similar global sensitivity to surface temperature change can be derived in GPCP, CMIP6, and AMIP6, providing confidence in both observed and simulated global mean precipitation change. Large regional trends with positive and negative values can readily be seen across the world in GPCP. AMIP6 can generally reproduce these large-scale spatial features. Comparisons with CMIP6 confirm the combined effects from anthropogenic greenhouse-gases (GHG) forcing and internal modes of climate variability such as the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). Limiting the PDO/AMO effect makes the trend patterns in GPCP residuals more similar to those in CMIP6, implying that the GHG effect would become more readily detectable in observed precipitation in the near future with regards to both global mean and regional precipitation changes. Furthermore, similar changes in precipitation seasonal range, especially over global lands, occur in GPCP, CMIP6, and AMIP6, suggesting that the GHG effect might already be discernible in certain aspects of precipitation change.

Mediterranean-type climates are defined by temperate, wet winters, and hot or warm dry summers and exist at the western edges of five continents in locations determined by the geography of winter storm tracks and summer subtropical anticyclones. The climatology, variability, and long-term changes in winter precipitation in Mediterranean-type climates, and the mechanisms for model-projected near-term future change, are analyzed. Despite commonalities in terms of location in the context of planetary-scale dynamics, the causes of variability are distinct across the regions. Internal atmospheric variability is the dominant source of winter precipitation variability in all Mediterranean-type climate regions, but only in the Mediterranean is this clearly related to annular mode variability. Ocean forcing of variability is a notable influence only for California and Chile. As a consequence, potential predictability of winter precipitation variability in the regions is low. In all regions, the trend in winter precipitation since 1901 is similar to that which arises as a response to changes in external forcing in the models participating in phase 5 of the Coupled Model Intercomparison Project. All Mediterranean-type climate regions, except in North America, have dried and the models project further drying over coming decades. In the Northern Hemisphere, dynamical processes are responsible: development of a winter ridge over the Mediterranean that suppresses precipitation and of a trough west of the North American west coast that shifts the Pacific storm track equatorward. In the Southern Hemisphere, mixed dynamic–thermodynamic changes are important that place a minimum in vertically integrated water vapor change at the coast and enhance zonal dry advection into Mediterranean-type climate regions inland.