Trends In Mean Precipitation Research Articles

Examining the Spatiotemporal Changes in the Annual, Seasonal, and Daily Rainfall Climatology of Puerto Rico

This study explores spatial and temporal changes in the rainfall climatology of Puerto Rico in order to identify areas where annual, seasonal or daily precipitation is increasing, decreasing, or remaining normal. Total annual, seasonal, and daily rainfall were retrieved from 23 historical rain gauges with consistent data for the 1956–2021 period. Mann–Kendall trend tests were done on the annual and seasonal rainfall series, and percentage change differences between two different climatologies (1956–1987 and 1988–2021) were calculated. Most of the stations did not exhibit statistically significant annual or seasonal trends in average rainfall. However, of the sites that did experience changes, most of them had statistically significant decreasing trends in mean precipitation. The annual, dry, and early wet season had more sites with negative trends when compared with positive trends, especially in the northwestern and southeastern region of the island. The late wet season was the only period with more sites showing statistically significant trends when compared with negative trends, specifically in the northern region of the island. Results for daily events show that extreme rainfall occurrences have generally decreased, especially in the western region of the island. When the 1955–1987 and 1988–2022 climatologies are compared, the results for annual average rainfall show two main regions with mean precipitation reductions, and those are the northwestern and southeastern areas of the island. The dry season was the only period with more areas exhibiting percentage increases in mean rainfall when the two climatologies were analyzed. The early and late wet season months exhibited similar patterns, with more areas on the island showing negative percentage decreases in average seasonal precipitation. The best predictor for the decreasing annual and seasonal trend in the northwest was a higher sea level pressure, and the variable that best explained the increasing trend in the northeast was total precipitable water.

Precipitation trends determine future occurrences of compound hot\u2013dry events

Compound hot–dry events—co-occurring hot and dry extremes—frequently cause damages to human and natural systems, often exceeding separate impacts from heatwaves and droughts. Strong increases in the occurrence of these events are projected with warming, but associated uncertainties remain large and poorly understood. Here, using climate model large ensembles, we show that mean precipitation trends exclusively modulate the future occurrence of compound hot–dry events over land. This occurs because local warming will be large enough that future droughts will always coincide with at least moderately hot extremes, even in a 2 °C warmer world. By contrast, precipitation trends are often weak and equivocal in sign, depending on the model, region and internal climate variability. Therefore, constraining regional precipitation trends will also constrain future compound hot–dry events. These results help to assess future frequencies of other compound extremes characterized by strongly different trends in the drivers.

Gross Discrepancies between Observed and Simulated Twentieth-to-Twenty-First-Century Precipitation Trends in Southeastern South America

AbstractSoutheastern South America (SESA; encompassing Paraguay, southern Brazil, Uruguay, and northern Argentina) experienced a 27% increase in austral summer precipitation from 1902 to 2019, one of the largest observed trends in seasonal precipitation globally. Previous research identifies Atlantic multidecadal variability and anthropogenic forcing from stratospheric ozone depletion and greenhouse gas emissions as key factors contributing to the positive precipitation trends in SESA. We analyze multimodel ensemble simulations from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP) and find that not only do Earth system models simulate positive SESA precipitation trends that are much weaker over the historical interval, but some models persistently simulate negative SESA precipitation trends under historical forcings. Similarly, 16-member ensembles from two atmospheric models forced with observed historical sea surface temperatures never simulate precipitation trends that even reach the lower bound of the observed trend’s range of uncertainty. Moreover, while future twenty-first-century projections from CMIP6 yield positive ensemble mean precipitation trends over SESA that grow with increasing greenhouse gas emissions, the mean forced response never exceeds the observed historical trend. Preindustrial control runs from CMIP6 indicate that some models do occasionally simulate centennial-scale trends in SESA that fall within the observational range, but most models do not. Results point to significant uncertainties in the attribution of anthropogenically forced influences on the observed increases in precipitation over SESA while also suggesting that internal decadal-to-centennial variability of unknown origin and not present in state-of-the-art models may have also played a large role in generating the twentieth-to-twenty-first-century SESA precipitation trend.

Performance of the RegCM4.6 for High-Resolution Climate and Extreme Simulations over Tibetan Plateau

This paper presents an evaluation of the Regional Climate Model version 4.6.1 (RegCM4) at a high-resolution simulation at 10 km applied over the Tibetan Plateau. This simulation covers the period from 1980 to 2010 and is nested in a RegCM4 simulation at 30-km resolution, which is driven by the main European Centre for Medium-Range Weather and Forecasting reanalysis (ERA-Interim reanalysis) dataset. A new daily observational dataset is employed as reference data to evaluate the temperature and precipitation simulations for the inner model domain and the five largest river basins that originated in the Tibetan Plateau (TP) (i.e., the source region of Yangtze River, Yellow River, Mekong River, Salween River, and Brahmaputra River). In comparison with the low-resolution model run (R30), the cold biases for the area-averaged temperature were reduced from −2.5 to −0.1° C and the wet biases in summer mean precipitation were reduced from 58% to 25% in the high-resolution model run (R10). The substantial warming trends and slight wetting trends were basically reproduced by both RegCM4 simulations. Annual mean precipitation trends from both simulations show a better agreement with the observations than the ERA-Interim, which underestimates the annual mean precipitation trends in most regions, whereas both the RegCM4 and ERA-Interim consistently underestimate the annual mean temperature trends when compared with the observations. In addition, the overall improvement in the modeling trends for annual mean temperature and precipitation in R10 is limited when compared with R30. The extreme precipitation was also captured reasonably in both RegCM4 simulations, and the better performance is detected in the R10 simulation. The findings above show that RegCM4 with a high-resolution of 10 km is capable of reproducing the major regional climate features over the TP, but a great deal of uncertainties still exist, especially in the subregion of the Brahmaputra River basin. Thus, the 10-km resolution simulation in RegCM4 may still not be fine enough to resolve the topoclimates over the complex Himalayan terrain in the Brahmaputra River basin.

NCA-LDAS: Overview and Analysis of Hydrologic Trends for the National Climate Assessment.

Terrestrial hydrologic trends over the conterminous United States are estimated for 1980-2015 using the National Climate Assessment Land Data Assimilation System (NCA-LDAS) reanalysis. NCA-LDAS employs the uncoupled Noah version 3.3 land surface model at 0.125°× 1258° forced with NLDAS-2 meteorology, rescaled Climate Prediction Center precipitation, and assimilated satellite-based soil moisture, snow depth, and irrigation products. Mean annual trends are reported using the nonparametric Mann-Kendall test at p < 0.1 significance. Results illustrate the interrelationship between regional gradients in forcing trends and trends in other land energy and water stores and fluxes. Mean precipitation trends range from +3 to +9 mm yr-1 in the upper Great Plains and Northeast to -1 to -9 mm yr-1 in the West and South, net radiation flux trends range from 10.05 to 10.20 W m-2 yr-1 in the East to -0.05 to -0.20 W m-2 yr-1 in the West, and U.S.-wide temperature trends average about +0.03 K yr-1. Trends in soil moisture, snow cover, latent and sensible heat fluxes, and runoff are consistent with forcings, contributing to increasing evaporative fraction trends from west to east. Evaluation of NCA-LDAS trends compared to independent data indicates mixed results. The RMSE of U.S.-wide trends in number of snow cover days improved from 3.13 to 2.89 days yr-1 while trend detection increased 11%. Trends in latent heat flux were hardly affected, with RMSE decreasing only from 0.17 to 0.16 W m-2 yr-1, while trend detection increased 2%. NCA-LDAS runoff trends degraded significantly from 2.6 to 16.1 mm yr-1 while trend detection was unaffected. Analysis also indicated that NCA-LDAS exhibits relatively more skill in low precipitation station density areas, suggesting there are limits to the effectiveness of satellite data assimilation in densely gauged regions. Overall, NCA-LDAS demonstrates capability for quantifying physically consistent, U.S. hydrologic climate trends over the satellite era.

Climate Change Amplification of Natural Drought Variability: The Historic Mid-Twentieth-Century North American Drought in a Warmer World

AbstractIn the mid-twentieth century (1948–57), North America experienced a severe drought forced by cold tropical Pacific sea surface temperatures (SSTs). If these SSTs recurred, it would likely cause another drought, but in a world substantially warmer than the one in which the original event took place. We use a 20-member ensemble of the GISS climate model to investigate the drought impacts of a repetition of the mid-twentieth-century SST anomalies in a significantly warmer world. Using observed SSTs and mid-twentieth-century forcings (Hist-DRGHT), the ensemble reproduces the observed precipitation deficits during the cold season (October–March) across the Southwest, southern plains, and Mexico and during the warm season (April–September) in the southern plains and the Southeast. Under analogous SST forcing and enhanced warming (Fut-DRGHT, ≈3 K above preindustrial), cold season precipitation deficits are ameliorated in the Southwest and southern plains and intensified in the Southeast, whereas during the warm season precipitation deficits are enhanced across North America. This occurs primarily from greenhouse gas–forced trends in mean precipitation, rather than changes in SST teleconnections. Cold season runoff deficits in Fut-DRGHT are significantly amplified over the Southeast, but otherwise similar to Hist-DRGHT over the Southwest and southern plains. In the warm season, however, runoff and soil moisture deficits during Fut-DRGHT are significantly amplified across the southern United States, a consequence of enhanced precipitation deficits and increased evaporative losses due to warming. Our study highlights how internal variability and greenhouse gas–forced trends in hydroclimate are likely to interact over North America, including how changes in both precipitation and evaporative demand will affect future drought.

Trends of precipitation characteristics in the Czech Republic over 1961–2012, their spatial patterns and links to temperature and the North Atlantic Oscillation

ABSTRACTDaily precipitation data from 162 stations in the Czech Republic over 1961–2012 are used to examine changes in seasonal precipitation indices, their spatial patterns and links to temperature and atmospheric circulation. The results show a divide between the western and eastern parts of the country as to trends in most precipitation characteristics in both winter and summer. Increases were more pronounced in the west, where Atlantic influences are stronger. In the eastern region, where continental and Mediterranean influences become more important, the trends are often inconclusive. Aggregated over the country as a whole, positive trends of mean precipitation as well as indices of precipitation intensity and extremes dominate in both winter and summer, and the mean precipitation trends are significant at a much larger percentage of stations than previously reported for 1961–2005. Spring is the only season with prevailing negative trends in mean precipitation and the number of wet days. The trends are least conclusive and close to zero in autumn. The trends differ for cold days (below the seasonal 25th percentile of daily maximum temperature) and warm days (above the seasonal 75th percentile). In contrast to overall winter trends, negative trends of mean precipitation, seasonal maxima and number of wet days prevail on cold days in winter. In summer, by far the most pronounced positive trends occur during warm days, when most precipitation comes from convective storms. Longitudinal dependency was found for most indices in winter and for mean precipitation and the number of wet days in summer. The different influence of the North Atlantic Oscillation on precipitation in the western and eastern parts of the Czech Republic together with positive (negative) trend of the North Atlantic Oscillation index in winter (summer) may contribute to the longitudinal dependency of the precipitation trends.

Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?

Abstract Quantile mapping bias correction algorithms are commonly used to correct systematic distributional biases in precipitation outputs from climate models. Although they are effective at removing historical biases relative to observations, it has been found that quantile mapping can artificially corrupt future model-projected trends. Previous studies on the modification of precipitation trends by quantile mapping have focused on mean quantities, with less attention paid to extremes. This article investigates the extent to which quantile mapping algorithms modify global climate model (GCM) trends in mean precipitation and precipitation extremes indices. First, a bias correction algorithm, quantile delta mapping (QDM), that explicitly preserves relative changes in precipitation quantiles is presented. QDM is compared on synthetic data with detrended quantile mapping (DQM), which is designed to preserve trends in the mean, and with standard quantile mapping (QM). Next, methods are applied to phase 5 of the Coupled Model Intercomparison Project (CMIP5) daily precipitation projections over Canada. Performance is assessed based on precipitation extremes indices and results from a generalized extreme value analysis applied to annual precipitation maxima. QM can inflate the magnitude of relative trends in precipitation extremes with respect to the raw GCM, often substantially, as compared to DQM and especially QDM. The degree of corruption in the GCM trends by QM is particularly large for changes in long period return values. By the 2080s, relative changes in excess of +500% with respect to historical conditions are noted at some locations for 20-yr return values, with maximum changes by DQM and QDM nearing +240% and +140%, respectively, whereas raw GCM changes are never projected to exceed +120%.

Trends in mean and extreme precipitation in the Mount Kenya region from observations and reanalyses

ABSTRACTLand and water management in semi‐arid regions requires detailed information on precipitation distribution, including extremes, and changes therein. Such information is often lacking. This paper describes statistics of mean and extreme precipitation in a unique data set from the Mount Kenya region, encompassing around 50 stations with at least 30 years of data. We describe the data set, including quality control procedures and statistical break detection. Trends in mean precipitation and extreme indices calculated from these data for individual rainy seasons are compared with corresponding trends in reanalysis products. From 1979 to 2011, mean precipitation decreased at 75% of the stations during the ‘long rains’ (March to May) and increased at 70% of the stations during the ‘short rains’ (October to December). Corresponding trends are found in the number of heavy precipitation days, and maximum of consecutive 5‐day precipitation. Conversely, an increase in consecutive dry days within both main rainy seasons is found. However, trends are only statistically significant in very few cases. Reanalysis data sets agree with observations with respect to interannual variability, while correlations are considerably lower for monthly deviations (ratios) from the mean annual cycle. While some products well reproduce the rainfall climatology and some the spatial trend pattern, no product reproduces both.

The cloud radiative effect on the atmospheric energy budget and global mean precipitation

This study seeks to explain the effects of cloud on changes in atmospheric radiative absorption that largely balance changes in global mean precipitation under climate change. The partial radiative perturbations (PRPs) due to changes in cloud and due to the effects of the pre-existing climatological cloud distribution on non-cloud changes, known as “cloud masking”, are calculated when atmospheric CO2 concentration is doubled for the HadSM3 and MIROC models and for a large ensemble of parameter perturbed models based on HadSM3. Because the effect of cloud on changes in atmospheric shortwave absorption is almost negligible, longwave fluxes are analysed alone. We find that the net effects of cloud masking and cloud PRP on atmospheric absorption are both substantial. For the tropics, our results are reviewed in light of hypotheses put forward to explain cloud and radiative flux changes. We find that the major effects of clouds on radiation change are linked to known physical processes that are quite consistently simulated by models. Cloud top height changes are quite well described by the fixed anvil temperature hypothesis of Hartmann and Larson; cloud base heights change little, remaining near the same pressure. Changes in cloud geographical location and cloud amount are significant, but play a smaller role in driving radiative flux changes. Finally, because clouds are a large source of modelling uncertainty, we consider whether resolving errors in cloud simulation could reconcile modelled global mean precipitation trends of about 1–3 %\(\hbox {K}^{-1}\) with some estimates of observed trends of 7 %\(\hbox {K}^{-1}\) or more. This would require the radiative effect of clouds to change from one that increases atmospheric radiative absorption by about \(0.5\,\hbox {Wm}^{-2}\,\hbox {K}^{-1}\) to one that decreases it by \(-3.5\,\hbox {Wm}^{-2}\,\hbox {K}^{-1}\). Based on our results, this seems difficult to achieve within our current rationale for the tropics at least.

Agent-Based Simulation of Holocene Monsoon Precipitation Patterns and Hunter-Gatherer Population Dynamics in Semi-arid Environments

Based on archaeological evidence from Kutch-Saurashtra (N Gujarat, NW India), we use agent-based modelling (ABM) to explore the persistence of hunter-gatherer (HG) groups in semi-arid environments in the mid and late Holocene. Agents interact within a realistic semi-arid environment dominated by the monsoon. Precipitation trends are modelled from instrumental records (1871–2008) calibrated with existing models for the Asian monsoon in the Holocene (c. 12 ka–present). Experiments aim at exploring dependencies between population dynamics and climate-driven environmental change (in terms of resource availability) for precipitation patterns at the local, regional and continental scales. Resources are distributed across a simplified ground model. Average yearly precipitation (AYP, i.e. mean) and variance in yearly precipitation (VYP, i.e. standard deviation) are the main parameters affecting resource availability in the simulations. We assess the effects of environmental change on HG populations at different timescales: (1) patterns of seasonal (inter-annual) resource availability, (2) effects of changes in mean precipitation trends over the long (Pleistocene–Holocene) and the mid (Holocene, millennial) periods, and (3) effects of intra-annual precipitation variability, i.e. changes in standard deviation from mean precipitation trends over the short period (annual to decadal). Simulations show that (1) strong seasonality is coherent with the persistence of HG populations in India, independently of the geographical scale of the precipitation models, (2) changes in AYP over the mid period (Holocene) are not sufficient to explain the disappearance of HG populations in Kutch-Saurashtra (K-S) 4 ka and (3) precipitation variability (VYP) over the short period (annual to decadal) is the main parameter affecting population performance and overall ecosystem dynamics. To date, sufficiently refined palaeoclimatic records do not exist for the study area, but higher VYP values 4 ka do not exclude the possibility that other factors may have driven the disappearance of HG populations in Kutch-Saurashtra.

Trends and correlations in annual extreme precipitation indices for mainland Portugal, 1941–2007

Precipitation extremes in mainland Portugal (south-western Europe) using daily precipitation data recorded in the period 1941–2007 (67 years) at 57 meteorological stations scattered across the area are studied at an annual scale. Trends in selected precipitation annual indices that are calculated from these data are investigated, in particular trends in the intensity, frequency and duration of extreme precipitation events. Special attention is dedicated to local and regional variability. The spatial correlations between the annual trends in mean precipitation and in the extremes are analysed. Moreover, the relationships between the variability of the North Atlantic Oscillation (NAO) index and several indices related to the frequency and intensity of the precipitation at the 57 stations were also investigated. Results show that several stations have predominantly negative tendencies in the precipitation indices, although the majority of stations did not show statistically significant change over time in the 1941–2007 period. At the regional level, the decreasing trend in the simple daily precipitation intensity index is the only one statistically significant at the 5 % level and appears to be related to the predominance of the positive phase of the NAO. For the period 1976–2007, the proportion of the total precipitation attributed to heavy and very heavy precipitation events increased and, consequently, daily precipitation events show a tendency to become more intense. Moreover, correlation analysis show that the most extreme events could be changing at a faster absolute rate in relation to the mean than more moderate events.

Evaluation of modeled changes in extreme precipitation in Europe and the Rhine basin

In this study, we investigate the change in multi-day precipitation extremes in late winter in Europe using observations and climate models. The objectives of the analysis are to determine whether climate models can accurately reproduce observed trends and, if not, to find the causes of the difference in trends. Similarly to an earlier finding for mean precipitation trends, and despite a lower signal to noise ratio, climate models fail to reproduce the increase in extremes in much of northern Europe: the model simulations do not cover the observed trend in large parts of this area. A dipole in the sea-level pressure trend over continental Europe causes positive trends in extremes in northern Europe and negative trends in the Iberian Peninsula. Climate models have a much weaker pressure trend dipole and as a result a much weaker (extreme) precipitation response. The inability of climate models to correctly simulate observed changes in atmospheric circulation is also primarily responsible for the underestimation of trends in the Rhine basin. When it has been adjusted for the circulation trend mismatch, the observed trend is well within the spread of the climate model simulations. Therefore, it is important that we improve our understanding of circulation changes, in particular related to the cause of the apparent mismatch between observed and modeled circulation trends over the past century.

When will trends in European mean and heavy daily precipitation emerge?

A multi-model ensemble of regional climate projections for Europe is employed to investigate how the time of emergence (TOE) for seasonal sums and maxima of daily precipitation depends on spatial scale. The TOE is redefined for emergence from internal variability only; the spread of the TOE due to imperfect climate model formulation is used as a measure of uncertainty in the TOE itself. Thereby, the TOE becomes a fundamentally limiting timescale and translates into a minimum spatial scale on which robust conclusions can be drawn about precipitation trends. Thus, minimum temporal and spatial scales for adaptation planning are also given. In northern Europe, positive winter trends in mean and heavy precipitation, and in southwestern and southeastern Europe, summer trends in mean precipitation already emerge within the next few decades. However, across wide areas, especially for heavy summer precipitation, the local trend emerges only late in the 21st century or later. For precipitation averaged to larger scales, the trend, in general, emerges earlier.

Impact of Antarctic Ozone Depletion and Recovery on Southern Hemisphere Precipitation, Evaporation, and Extreme Changes

The possible impact of Antarctic ozone depletion and recovery on Southern Hemisphere (SH) mean and extreme precipitation and evaporation is examined using multimodel output from the Climate Model Intercomparison Project 3 (CMIP3). By grouping models into four sets, those with and without ozone depletion in twentieth-century climate simulations and those with and without ozone recovery in twenty-first-century climate simulations, and comparing their multimodel-mean trends, it is shown that Antarctic ozone forcings significantly modulate extratropical precipitation changes in austral summer. The impact on evaporation trends is however minimal, especially in twentieth-century climate simulations. In general, ozone depletion has increased (decreased) precipitation in high latitudes (midlatitudes), in agreement with the poleward displacement of the westerly jet and associated storm tracks by Antarctic ozone depletion. Although weaker, the opposite is also true for ozone recovery. These precipitation changes are primarily associated with changes in light precipitation (1–10 mm day−1). Contributions by very light precipitation (0.1–1 mm day−1) and moderate-to-heavy precipitation (&gt;10 mm day−1) are minor. Likewise, no systematic changes are found in extreme precipitation events, although extreme surface wind events are highly sensitive to ozone forcings. This result indicates that, while extratropical mean precipitation trends are significantly modulated by ozone-induced large-scale circulation changes, extreme precipitation changes are likely more sensitive to thermodynamic processes near the surface than to dynamical processes in the free atmosphere.

Trend analysis in Icelandic discharge, temperature and precipitation series by parametric methods

This paper presents results of analyses by parametric methods of annual means of temperature, precipitation and discharge, and of seasonal maximum precipitation at 17, 28 and 10 Icelandic stations, respectively, for the period 1961–2000. Trends in mean seasonal temperature and precipitation are in broad agreement with results found by other authors using other methods. A positive trend appears in both mean annual temperature and mean temperatures in most seasons. Annual mean precipitation trends are positive in most seasons except for negative trends in the September–November season in the south. Additionally, positive trends appear in maximum one-, three- and five-day precipitation, both during the spring and autumn, except at a group of stations in central Iceland. Some of the positive trends in mean annual and seasonal precipitation may, however, be attributed to the positive trend in temperature which may have influenced gauge catch. Trends in mean annual and seasonal discharge are small and statistically insignificant; the trends found in temperature and precipitation do not all relate directly to trends in discharge but suggest hypotheses for further study of the relationships between them.

Secular trends in daily precipitation characteristics: greenhouse gas simulation with a coupled AOGCM

Secular trends of daily precipitation characteristics are considered in the transient climate change experiment with a coupled atmosphere-ocean general circulation model ECHAM4/OPYC3 for 1900-2099. The climate forcing is due to increasing concentrations of the greenhouse gases in the atmosphere. Mean daily precipitation, precipitation intensity, probability of wet days and parameters of the gamma distribution are analyzed. Particular attention is paid to the changes of heavy precipitation, Analysis of the annual mean precipitation trends for 1900-1999 revealed general agreement with observations with significant positive trends in mean precipitation over continental areas. In the 2000-2099 period precipitation trend patterns followed the tendency obtained for 1900-1999 but with significantly increased magnitudes. Unlike the annual mean precipitation trends for which negative values were found for some continental areas, the mean precipitation intensity and scale parameter of the fitted gamma distribution increased over all land territories . Negative trends in the number of wet days were found over most of the land areas except high latitudes in the Northern Hemisphere. The shape parameter of the gamma distribution in general revealed a slight negative trend in the areas of the precipitation increase. Investigation of daily precipitation revealed an unproportional increase of heavy precipitation events for the land areas including local maxima in Europe and the eastern United States.