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Future projections of precipitation at regional scales are vital to inform climate change adaptation activities. Therefore, is it important to quantify projected changes and associated uncertainty, and understand model processes responsible. This paper addresses these challenges for southern Africa and the adjacent Indian Ocean focusing on the local wet season. Precipitation projections for the end of the twenty-first century indicate a pronounced dipole pattern in the CMIP5 multimodel mean. The dipole indicates future wetting (drying) to the north (south) of the climatological axis of maximum rainfall, implying a northward shift of the ITCZ and south Indian Ocean convergence zone that is not consistent with a simple "wet get wetter" pattern. This pattern is most pronounced in early austral summer, suggesting a later and shorter wet season over much of southern Africa. Using a decomposition method we determine physical mechanisms underlying this dipole pattern of projected change, and the associated intermodel uncertainty. The projected dipole pattern is largely associated with the dynamical component of change indicative of shifts in the location of convection. Over the Indian Ocean, this apparent northward shift in the ITCZ may reflect the response to changes in the north-south SST gradient over the Indian Ocean, consistent with a "warmest get wetter" mechanism. Over land subtropical drying is relatively robust, particularly in the early wet season. This has contributions from dynamical shifts in the location of convection, which may be related to regional SST structures in the southern Indian Ocean, and the thermodynamic decline in relative humidity. Implications for understanding and potentially constraining uncertainty in projections are discussed. [ABSTRACT FROM AUTHOR]

This paper scrutinizes the zonal oscillation of the western North Pacific subtropical high (WNPSH) via diagnosing its two extreme phases, which are defined by the top 10% strongest (positive phase) and the weakest (negative phase) WNPSH index (WNPSHI) days during summers in 1979–2016. Key findings include the following: a tripole pattern consisting of intensified (weakened) precipitation over the Maritime Continent and the East Asian summer monsoon regions, and suppressed (strengthened) precipitation over the western North Pacific summer monsoon region during positive (negative) WNPSH phases; a westward movement of WNPSH-induced precipitation anomalies that subsequently affects eastern China, Japan, and the Korean Peninsula at different time lags; an OLR–vorticity pattern explained by atmospheric responses to thermal sources is suggested to drive the oscillation; and the competitive interaction of local air–sea feedbacks, especially during the positive phase. In addition, moderate-to-strong positive correlations between the WNPSHI and the Niño-3.4 index are found on 1–2-, 2–3-, and 3–6-yr time scales; both exhibit decadal shifts to a higher-frequency mode, suggesting the intensification of both the zonal WNPSH oscillation and the ENSO under the changing climate and their close interdecadal association. A nonlinear quasi-biennial WNPSH–ENSO relationship is identified: the positive (negative) WNPSH phase sometimes occurs during 1) a decaying El Niño (La Niña) in the preceding summer/autumn, and/or 2) a developing La Niña (El Niño) in the current summer/autumn. A full ENSO transition from moderate-to-strong El Niño to La Niña is often seen during the positive phase, offering potential in predicting ENSO events and extreme WNPSH phases and thereby the summer monsoon rainfall in East Asia. [ABSTRACT FROM AUTHOR]

The IPCC Fifth Assessment Report highlighted large uncertainty in European precipitation changes in the coming century. This paper investigates the sources of intermodel differences using CMIP5 model European precipitation data. The contribution of atmospheric circulation to differences in precipitation trends is investigated by applying cluster analysis to daily mean sea level pressure (MSLP) data. The resulting classification is used to reconstruct monthly precipitation time series, thereby isolating the component of precipitation variability directly related to atmospheric circulation. Reconstructed observed precipitation and reconstructions of simulated historical and projection data are well correlated with the original precipitation series, showing that circulation variability accounts for a substantial fraction of European precipitation variability. Removing the reconstructed precipitation from the original precipitation leaves a residual component related to noncirculation effects (and any small remaining circulation effects). Intermodel spread in residual future European precipitation trends is substantially reduced compared to the spread of the original precipitation trends. Uncertainty in future atmospheric circulation accounts for more than half of the intermodel variance in twenty-first-century precipitation trends for winter months for both northern and southern Europe. Furthermore, a substantial part of this variance is related to different forced dynamical responses in different models and is therefore potentially reducible. These results highlight the importance of understanding future changes in atmospheric dynamics in achieving more robust projections of regional climate change. Finally, the possible dynamical mechanisms that may drive the future differences in regional circulation and precipitation are illustrated by examining simulated teleconnections with tropical precipitation. [ABSTRACT FROM AUTHOR]

Few if any high-resolution (annually resolved) paleoclimate records are available for the Hawaiian Islands prior to ~1850 CE, after which some instrumental records start to become available. This paper shows how atmospheric teleconnection patterns between North America and the northeastern North Pacific (NNP) allow for reconstruction of Hawaiian Islands rainfall using remote proxy information from North America. Based on a newly available precipitation dataset for the state of Hawaii and observed and reconstructed December-February (DJF) sea level pressures (SLPs) in the North Pacific Ocean, the authors make use of a strong relationship between winter SLP variability in the northeast Pacific and corresponding DJF Hawaii rainfall variations to reconstruct and evaluate that season's rainfall over the period 1500-2012 CE. A general drying trend, though with substantial decadal and longer-term variability, is evident, particularly during the last ~160 years. Hawaiian Islands rainfall exhibits strong modulation by El Niño-Southern Oscillation (ENSO), as well as in relation to Pacific decadal oscillation (PDO)-like variability. For significant periods of time, the reconstructed large-scale changes in the North Pacific SLP field described here and by construction the long-term decline in Hawaiian winter rainfall are broadly consistent with long-term changes in tropical Pacific sea surface temperature (SST) based on ENSO reconstructions documented in several other studies, particularly over the last two centuries. Also noted are some rather large multidecadal fluctuations in rainfall (and hence in NNP SLP) in the eighteenth century of undetermined provenance. [ABSTRACT FROM AUTHOR]

The response over West Africa to uniform warming of the Atlantic Ocean is analyzed using idealized simulations with a regional climate model. With warming of 1 and 1.5 K, rainfall rates increase by 30%-50% over most of West Africa. With Atlantic warming of 2 K and higher, coastal precipitation increases but Sahel rainfall decreases substantially. This nonlinear response in Sahel rainfall is the focus of this analysis. Atlantic warming is accompanied by decreases in low-level geopotential heights in the Gulf of Guinea and in the large-scale meridional geopotential height gradient. This leads to easterly wind anomalies in the central Sahel. With Atlantic warming below 2 K, these easterly anomalies support moisture transport from the Gulf of Guinea and precipitation increases. With Atlantic warming over 2 K, the easterly anomalies reverse the westerly flow over the Sahel. The resulting dry air advection into the Sahel reduces precipitation. Increased low-level moisture provides moist static energy to initiate convection with Atlantic warming at 1.5 K and below, while decreased moisture and stable thermal profiles suppress convection with additional warming. In all simulations, the southerly monsoon flow onto the Guinean coast is maintained and precipitation in that region increases. The relevance of these results to the global warming problem is limited by the focus on Atlantic warming alone. However, confident prediction of climate change requires an understanding of the physical processes of change, and this paper contributes to that goal. [ABSTRACT FROM AUTHOR]

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 2 global coupled climatic model has been used to generate a 10 000-yr simulation of “present” climate. The resultant dataset has been used to investigate a number of aspects of extremes associated with annual mean rainfall. Multimillennial time series of normalized rainfall amounts for selected points are used to highlight secular variability, spatial variations, and the differences between pluvial and drought conditions. Global distributions are also presented for selected rainfall characteristics, including the frequency of occurrence of specified rainfall anomalies with annual durations, the frequency of occurrence of 5-yr sequences of specified rainfall anomalies, and the maximum and minimum normalized rainfall amounts attained in the simulation. Such features cannot be obtained from observations because of their limited duration. A case study is also made of a megadrought over the southwestern United States, together with an analysis of the associated causal mechanisms. Given the exclusion of all external forcing from the model, it is concluded that the extreme annual mean rainfall extremes presented in the paper are attributable to stochastic events. [ABSTRACT FROM AUTHOR]

This paper discusses a study of temperature and precipitation indices that may be suitable for the early detection of anthropogenic change in climatic extremes. Anthropogenic changes in daily minimum and maximum temperature and precipitation over land simulated with two different atmosphere–ocean general circulation models are analyzed. The use of data from two models helps to assess which changes might be robust between models. Indices are calculated that scan the transition from mean to extreme climate events within a year. Projected changes in temperature extremes are significantly different from changes in seasonal means over a large fraction (39%–66%) of model grid points. Therefore, the detection of changes in seasonal mean temperature cannot be substituted for the detection of changes in extremes. The estimated signal-to-noise ratio for changes in extreme temperature is nearly as large as for changes in mean temperature. Both models simulate extreme precipitation changes that are stronger than the corresponding changes in mean precipitation. Climate change patterns for precipitation are quite different between the models, but both models simulate stronger increases of precipitation for the wettest day of the year (4.1% and 8.8%, respectively, over land) than for annual mean precipitation (0% and 0.7%, respectively). A signal-to-noise analysis suggests that changes in moderately extreme precipitation should become more robustly detectable given model uncertainty than changes in mean precipitation. [ABSTRACT FROM AUTHOR]

Over the past decades, significant changes in temperature and precipitation have been observed, including changes in the mean and extremes. It is critical to understand the trends in hydroclimatic extremes and how they may change in the future as they pose substantial threats to society through impacts on agricultural production, economic losses, and human casualties. In this study, we analyzed projected changes in the characteristics, including frequency, seasonal timing, and maximum spatial and temporal extent, as well as severity, of extreme temperature and precipitation events, using the severity–area–duration (SAD) method and based on a suite of 37 climate models archived in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Comparison between the CMIP5 model estimated extreme events and an observation-based dataset [Princeton Global Forcing (PGF)] indicates that climate models have moderate success in reproducing historical statistics of extreme events. Results from the twenty-first-century projections suggest that, on top of the rapid warming indicated by a significant increase in mean temperature, there is an overall wetting trend in the Northern Hemisphere with increasing wet extremes and decreasing dry extremes, whereas the Southern Hemisphere will have more intense wet extremes. The timing of extreme precipitation events will change at different spatial scales, with the largest change occurring in southern Asia. The probability of concurrent dry/hot and wet/hot extremes is projected to increase under both RCP4.5 and RCP8.5 scenarios, whereas little change is detected in the probability of concurrent dry/cold events and only a slight decrease of the joint probability of wet/cold extremes is expected in the future. [ABSTRACT FROM AUTHOR]

In China, summer precipitation contributes a major part of the total precipitation amount in a year and has major impacts on society and human life. Whether any changes in summer precipitation are affected by external forcing on the climate system is an important issue. In this study, an optimal fingerprinting method was used to compare the observed changes of total, heavy, moderate, and light precipitation in summer derived from newly homogenized observation data with the simulations from multiple climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). The results demonstrate that the anthropogenic forcing signal can be detected and separated from the natural forcing signal in the observed increase of seasonal accumulated precipitation amount for heavy precipitation in summer in China and eastern China (EC). The simulated changes in heavy precipitation are generally consistent with observed change in China but are underestimated in EC. When the changes in precipitation of different intensities are considered simultaneously, the human influence on simultaneous changes in moderate and light precipitation can be detected in China and EC in summer. Changes attributable to anthropogenic forcing explain most of the observed regional changes for all categories of summer precipitation, and natural forcing contributes little. In the future, with increasing anthropogenic influence, the attribution-constrained projection suggests that heavy precipitation in summer will increase more than that from the model raw outputs. Society may therefore face a higher risk of heavy precipitation in the future. [ABSTRACT FROM AUTHOR]

Estimates of present and future extreme sub-hourly rainfall are derived from a daily spatial followed by a sub-daily temporal downscaling, the latter of which incorporates a novel, and crucial, temperature sensitivity. Specifically, daily global climate fields are spatially downscaled to local temperature T and precipitation P, which are then disaggregated to a temporal resolution of 10 min using a multiplicative random cascade model. The scheme is calibrated and validated with a group of 21 station records of 10-min resolution in Germany. The cascade model is used in the classical (denoted as MC) and in the new T-sensitive (MC+) version, which respects local Clausius–Clapeyron (CC) effects such as CC scaling. Extreme P is positively biased in both MC versions. Observed T sensitivity is absent in MC but well reproduced by MC+. Long-term positive trends in extreme sub-hourly P are generally more pronounced and more significant in MC+ than in MC. In units of 10-min rainfall, observed centennial trends in annual exceedance counts (EC) of P > 5 mm are +29% and in 3-yr return levels (RL) +27%. For the RCP4.5-simulated future, higher extremes are projected in both versions MC and MC+: per century, EC increases by 30% for MC and by 83% for MC+; the RL rises by 14% for MC and by 33% for MC+. Because the projected daily P trends are negligible, the sub-daily signal is mainly driven by local temperature. [ABSTRACT FROM AUTHOR]

Trends in mean and extreme annual and seasonal temperature and precipitation over the 1951–2015 period were calculated for 57 stations in 20 western Pacific Ocean island countries and territories. The extremes indices are those of the World Meteorological Organization Expert Team on Sector-Specific Climate Indices. The purpose of the expert team and indices is to promote the use of globally consistent climate indices to highlight variability and trends in climate extremes that are of particular interest to socioeconomic sectors and to help to characterize the climate sensitivity of various sectors. Prior to the calculation of the monthly means and indices, the data underwent quality control and homogeneity assessment. A rise in mean temperature occurred at most stations, in all seasons, and in both halves of the study period. The temperature indices also showed strong warming, which for the majority was strongest in December–February and weakest in June–August. The absolute and percentile-based indices show the greatest warming at the upper end of the distribution. While changes in precipitation were less consistent and trends were generally weak at most locations, declines in both total and extreme precipitation were found in southwestern French Polynesia and the southern subtropics. There was a decrease in moderate- to high-intensity precipitation events, especially those experienced over multiple days, in southwestern French Polynesia from December to February. Strong drying trends have also been identified in the low- to moderate-extreme indices in the June–August and September–November periods. These negative trends contributed to an increase in the magnitude of meteorological drought in both subregions. [ABSTRACT FROM AUTHOR]

The mean precipitation along the U.S. West Coast exhibits a pronounced seasonality change under warming. Here we explore the characteristics of the seasonality change and investigate the underlying mechanisms, with a focus on quantifying the roles of moisture (thermodynamic) versus circulation (dynamic). The multimodel simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) show a simple "wet-get-wetter" response over Washington and Oregon but a sharpened seasonal cycle marked by a stronger and narrower wet season over California. Moisture budget analysis shows that changes in both regions are predominantly caused by changes in the mean moisture convergence. The thermodynamic effect due to the mass convergence of increased moisture dominates the wet-get-wetter response over Washington and Oregon. In contrast, mean zonal moisture advection due to seasonally dependent changes in land–sea moisture contrast originating from the nonlinear Clausius–Clapeyron relation dominates the sharpened wet season over California. More specifically, the stronger climatological land–sea thermal contrast in winter with warmer ocean than land results in more moisture increase over ocean than land under warming and hence wet advection to California. However, in fall and spring, the future change of land–sea thermal contrast with larger warming over land than ocean induces an opposite moisture gradient and hence dry advection to California. These results have important implications for projecting changes in the hydrological cycle of the U.S. West Coast. [ABSTRACT FROM AUTHOR]

Confident model projections of regional climate, in particular precipitation, could be very useful for designing climate change adaptation, particularly for vulnerable regions such as the Sahel. However, there is an extremely large uncertainty in the future Sahel rainfall projections made by current climate models. In this study, we find a close relationship between the future Sahel rainfall projections and present rainfall simulation biases in South Asia and the western North Pacific in summer, using the historical simulations and future projections of phase 5 of the Coupled Model Intercomparison Project (CMIP5). This future–present relationship can be used to calibrate Sahel rainfall projections since historical simulation biases can be much more reliably estimated than future change. The accordingly calibrated results show a substantial increase in both precipitation and precipitation minus evaporation in the future Sahel, in comparison with the multimodel ensemble (MME) result. This relationship between the historical rainfall bias and future Sahel rainfall projection is suggested to lie with the different schemes of convective parameterization among models: some schemes tend to result in both overestimated (underestimated) historical rainfall in South Asia (the western North Pacific) and enhanced future Sahel rainfall projection, while other schemes result in the opposite. [ABSTRACT FROM AUTHOR]

Precipitation extremes are expected to increase by 7% per degree of warming according to the Clausius–Clapeyron (CC) relation. However, this scaling behavior is inappropriate for high temperatures and short-duration precipitation extremes. Here, daily data from 702 stations during 1951–2014 and hourly data from 8 stations during 2000–15 are used to examine and explain this behavior in China. Both daily and hourly precipitation extremes exhibit an increase in temperature dependency at lower temperatures. The CC scaling transitions from positive to negative rates with temperatures greater than 25°C. Unlike the increase in daily data, which is similar to single-CC (1CC) scaling, the increase in hourly data resembles super-CC (2CC) scaling for temperatures greater than 13°C. Results show that the precipitation extremes are controlled by water vapor for a given temperature. At lower temperatures, precipitation extremes exhibit a positive linear dependence on daily actual vapor pressure whose value is almost equal to the saturated vapor pressure at a given temperature. At higher temperatures, actual vapor pressure has difficulty maintaining a consistent increasing rate because of the exponential increasing of the saturated vapor pressure. Higher temperatures result in larger vapor pressure deficits, which lead to sharp decreases in precipitation extremes. Similar scaling behaviors are obtained in 10 river basins over China, where the breaking point temperature increases from 17°C along the northwest inland area to 25°C along the southeast coast. These behaviors demonstrate that precipitation extremes are firmly linked to temperature when there is sufficient moisture at lower temperatures and limited by insufficient moisture at higher temperatures. Overall, precipitation extreme events require more attention in a warming climate. [ABSTRACT FROM AUTHOR]

A warming climate is expected to intensify extreme precipitation, and climate models project a general intensification of annual extreme precipitation in most regions of the globe throughout the twenty-first century. We investigate the robustness of this future intensification over land across different models, regions, and seasons and evaluate the role of model interdependencies in the CMIP5 ensemble. Strong similarities in extreme precipitation changes are found between models that share atmospheric physics, turning an ensemble of 27 models into around 14 projections. We find that future annual extreme precipitation intensity increases in the majority of models and in the majority of land grid cells, from the driest to the wettest regions, as defined by each model’s precipitation climatology. The intermodel spread is generally larger over wet than over dry regions, smaller in the dry season compared to the wet season and at the annual scale, and largely reduced in extratropical compared to tropical regions and at the global scale. For each model, the future increase in annual and seasonal maximum daily precipitation amounts exceeds the range of simulated internal variability in the majority of land grid cells. At both annual and seasonal scales, however, there are a few regions where the change is still within the background climate noise, but their size and location differ between models. In extratropical regions, the signal-to-noise ratio of projected changes in extreme precipitation is particularly robust across models because of a similar change and background climate noise, whereas projected changes are less robust in the tropics. [ABSTRACT FROM AUTHOR]

Climate change will impact both mean and extreme precipitation, having potentially significant consequences on water resources. The implementation of efficient adaptation measures must rely on the development of reliable projections of future precipitation and on the assessment of their related uncertainty. Natural climate variability is a key uncertainty component, which can result in apparent decadal trends that may be greater or lower than the long-term underlying anthropogenic climate change trend. The goal of the present study is to assess how natural climate variability affects the ability to detect the climate change signal for mean and extreme precipitation. Annual and seasonal total precipitation are used as indicators of the mean, whereas annual and seasonal maximum daily precipitation are used as indicators of extremes. This is done using the CanESM2 50-member and CESM1 40-member large ensembles of simulations over the 1950-2100 period. At the local scale, results indicate that natural climate variability will dominate the uncertainty for annual and seasonal extreme precipitation going up to the end of the century in many parts of the world. The climate change signal can, however, be reliably detected much earlier at the regional scale for extreme precipitation. In the case of annual and seasonal total precipitation, the climate change signal can be reliably detected at the local scale without resorting to a regional analysis. Nonetheless, natural climate variability can impede the detection of the anthropogenic climate change signal until the middle to late century in many parts of the world for mean and extreme precipitation. [ABSTRACT FROM AUTHOR]

The question of when the influence of climate change on U.K. rainfall extremes may be detected is important from a planning perspective, providing a time scale for necessary climate change adaptation measures. Short-duration intense rainfall is responsible for flash flooding, and several studies have suggested an amplified response to warming for rainfall extremes on hourly and subhourly time scales. However, there are very few studies examining the detection of changes in subdaily rainfall. This is due to the high cost of very high-resolution (kilometer scale) climate models needed to capture hourly rainfall extremes and to a lack of sufficiently long, high-quality, subdaily observational records. Results using output from a 1.5-km climate model over the southern United Kingdom indicate that changes in 10-min and hourly precipitation emerge before changes in daily precipitation. In particular, model results suggest detection times for short-duration rainfall intensity in the 2040s in winter and the 2080s in summer, which are, respectively, 5–10 years and decades earlier than for daily extremes. Results from a new quality-controlled observational dataset of hourly rainfall over the United Kingdom do not show a similar difference between daily and hourly trends. Natural variability appears to dominate current observed trends (including an increase in the intensity of heavy summer rainfall over the last 30 years), with some suggestion of larger daily than hourly trends for recent decades. The expectation of the reverse, namely, larger trends for short-duration rainfall, as the signature of underlying climate change has potentially important implications for detection and attribution studies. [ABSTRACT FROM AUTHOR]

Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land-atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land-atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land-atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer. [ABSTRACT FROM AUTHOR]

This study introduces a new daily high-resolution land-only observational gridded dataset, called SA-OBS, for precipitation and minimum, mean, and maximum temperature covering Southeast Asia. This dataset improves upon existing observational products in terms of the number of contributing stations, in the use of an interpolation technique appropriate for daily climate observations, and in making estimates of the uncertainty of the gridded data. The dataset is delivered on a 0.25° × 0.25° and a 0.5° × 0.5° regular latitude-longitude grid for the period 1981-2014. The dataset aims to provide best estimates of grid square averages rather than point values to enable direct comparisons with regional climate models. Next to the best estimates, daily uncertainties are quantified. The underlying daily station time series are collected in cooperation between meteorological services in the region: the Southeast Asian Climate Assessment and Dataset (SACA&D). Comparisons are made with station observations and other gridded station or satellite-based datasets (APHRODITE, CMORPH, TRMM). The comparisons show that vast differences exist in the average daily precipitation, the number of rainy days, and the average precipitation on a wet day between these datasets. SA-OBS closely resembles the station observations in terms of dry/wet frequency, the timing of precipitation events, and the reproduction of extreme precipitation. New versions of SA-OBS will be released when the station network in SACA&D has grown further. [ABSTRACT FROM AUTHOR]

Climate models robustly imply that some significant change in precipitation patterns will occur. Models consistently project that the intensity of individual precipitation events increases by approximately 6%-7% K−1, following the increase in atmospheric water content, but that total precipitation increases by a lesser amount (1%-2% K−1 in the global average in transient runs). Some other aspect of precipitation events must then change to compensate for this difference. The authors develop a new methodology for identifying individual rainstorms and studying their physical characteristics-including starting location, intensity, spatial extent, duration, and trajectory-that allows identifying that compensating mechanism. This technique is applied to precipitation over the contiguous United States from both radar-based data products and high-resolution model runs simulating 80 years of business-as-usual warming. In the model study the dominant compensating mechanism is a reduction of storm size. In summer, rainstorms become more intense but smaller; in winter, rainstorm shrinkage still dominates, but storms also become less numerous and shorter duration. These results imply that flood impacts from climate change will be less severe than would be expected from changes in precipitation intensity alone. However, these projected changes are smaller than model-observation biases, implying that the best means of incorporating them into impact assessments is via 'data-driven simulations' that apply model-projected changes to observational data. The authors therefore develop a simulation algorithm that statistically describes model changes in precipitation characteristics and adjusts data accordingly, and they show that, especially for summertime precipitation, it outperforms simulation approaches that do not include spatial information. [ABSTRACT FROM AUTHOR]

As the planet warms, climate models predict that rain will become heavier but less frequent and that the circulation will weaken. Here, two heuristic models relating moisture, vertical velocity, and rainfall distributions are developed-one in which the distribution of vertical velocity is prescribed and another in which it is predicted. These models are used to explore the response to warming and moistening as well as changes in circulation, atmospheric energy budget, and stability. Some key assumptions of the models include that relative humidity is fixed within and between climate states and that stability is constant within each climate state. The first model shows that an increase in skewness of the vertical velocity distribution is crucial for capturing salient characteristics of the changing distribution of rain, including the muted rate of mean precipitation increase relative to extremes and the decrease in the total number or area of rain events. The second model suggests that this increase in the skewness of the vertical velocity arises from the asymmetric impact of latent heating on vertical motion. [ABSTRACT FROM AUTHOR]

Climate-model simulations predict an intensification of extreme precipitation in almost all areas of the world under global warming. Local variations in the magnitude of this intensification are evident in these simulations, but most previous efforts to understand the factors responsible for the changes in extreme precipitation focused on zonal averages and neglected zonal variations, leading to uncertainties in the understanding and estimation of regional responses. Here the spatial heterogeneity of the warming-induced response of midlatitude extreme precipitation is studied in climate-model simulations with idealized orography on the western margins of otherwise flat continents. It is shown that the sensitivity of extreme precipitation to warming (i.e., its fractional rate of increase in intensity with global-mean surface temperature) is ~3% K−1 lower over the mountains than the oceans and plains. This difference in sensitivity is primarily produced by differences in the dynamics governing vertical ascent over the three regions. In these extreme events, mountain-wave dynamics control the moist ascent over the mountains, and the sensitivity of this ascent to global warming is mainly controlled by changes in upper-level dry static stability and the cross-mountain winds. In contrast, midlatitude cyclone dynamics govern moist ascent over the oceans and plains. Ascending motions in intense midlatitude cyclones are sensitive to the ratio of the moist static stability in their saturated cores to the dry stability in surrounding regions. This ratio decreases in the warmer world, intensifying the maximum vertical velocities while reducing the horizontal extent of the regions of the rising air within the cyclone. [ABSTRACT FROM AUTHOR]

Projections of three important seasonal rainfall parameters-total precipitation (), wet-day mean () and wet-day frequency ()-considered to be relevant to crop agriculture were performed. Links between large-scale climate variables and local precipitation in Tanzania were investigated during the March-May (MAM), October-December (OND), and December-April (DJFMA) rainfall seasons. Variables found to have strong links were used to downscale the local precipitation for three future periods; near term, midcentury, and end of century. Downscaling models for , and were calibrated using observed large-scale seasonal rainfall and projected downscaled parameters were obtained based on rainfall simulations from ensembles of GCMs. The models' skill scores were found to be sensitive to the domain size and number of leading EOFs used. The common EOF method employed in the downscaling modulated the skills depending on the GCMs used. The spread in the rainfall projections was found to be larger in OND and moderate in MAM and DJFMA. The multimodel mean projections in response to two RCPs (RCP4.5 and RCP8.5) suggest a shift toward wetter (drier) conditions () for OND (DJFMA) for all three periods. There is no uniform projection for MAM; some stations are projected to feature wetter and some drier conditions. In the midcentury and end of century, there is an increase of precipitation to about 40% for some areas getting OND rainfall and a decrease of precipitation up to about 10% for some areas getting MAM or DJFMA rainfall. Generally, the magnitude of change strongly differs across the areas. [ABSTRACT FROM AUTHOR]

This study presents climate change results from the North American Regional Climate Change Assessment Program (NARCCAP) suite of dynamically downscaled simulations for the North American monsoon system in the southwestern United States and northwestern Mexico. The focus is on changes in precipitation and the processes driving the projected changes from the regional climate simulations and their driving coupled atmosphere-ocean global climate models. The effect of known biases on the projections is also examined. Overall, there is strong ensemble agreement for a large decrease in precipitation during the monsoon season; however, this agreement and the magnitude of the ensemble-mean change is likely deceiving, as the greatest decreases are produced by the simulations that are the most biased in the baseline/current climate. Furthermore, some of the greatest decreases in precipitation are being driven by changes in processes/phenomena that are less credible (e.g., changes in El Niño-Southern Oscillation, when it is initially not simulated well). In other simulations, the processes driving the precipitation change may be plausible, but other biases (e.g., biases in low-level moisture or precipitation intensity) appear to be affecting the magnitude of the projected changes. The most and least credible simulations are clearly identified, while the other simulations are mixed in their abilities to produce projections of value. [ABSTRACT FROM AUTHOR]

Indian summer monsoon rainfall was examined in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenarios (SRES; B1) and a similar greenhouse gas scenario, the new representative concentration pathways (RCPs; RCP4.5). The rainfall change in the climate model projections through remotely induced changes in precipitation processes and through changes in precipitation efficiency processes was discussed. To that end, two model setups were applied: 1) the regional climate model (RCM) Consortium for Small-Scale Modelling in Climate Mode (COSMO-CLM), nested in the global climate model (GCM) ECHAM5/Max Planck Institute ocean model (ECHAM5/MPIOM), applying the greenhouse gas scenario B1; and 2) the RCM nested in a newer version of the GCM, ECHAM6/MPIOM, incorporating the RCP4.5 scenario. Both GCM simulations showed a slight increase in precipitation over central India toward the end of the twenty-first century. This slight increase was the result of two largely compensating changes: increase of remotely induced precipitation and decrease of precipitation efficiency. The RCM with the scenario RCP4.5 followed this trend, but with smaller changes. However, the RCM with B1 showed a decreasing trend in precipitation because of a slightly larger absolute change of the reduced precipitation efficiency compared to the change caused by the remote processes. Changes of these processes in the scenario simulations were larger than the natural variability, as simulated in an unperturbed preindustrial greenhouse gas control (CTL) climate simulation. Results indicated that the projection of the Indian summer monsoon rainfall is still a key challenge for both the GCM and the RCM. [ABSTRACT FROM AUTHOR]

An analysis of the October 2013-September 2014 precipitation in the western United States and in particular over the California-Nevada region suggests this anomalously dry season, while extreme, is not unprecedented in comparison with the approximately 120-yr-long instrumental record of water year (WY; October-September) totals and in comparison with a 407-yr WY precipitation reconstruction dating back to 1571. Over this longer period, nine other years are known or estimated to have been nearly as dry or drier than WY 2014. The 3-yr deficit for WYs 2012-14, which in California exceeded the annual mean precipitation, is more extreme but also not unprecedented, occurring three other times over the past approximate 440 years in the reconstruction. WY precipitation has also been deficient on average for the past 14 years, and such a run of predominantly dry WYs is also a rare occurrence in the authors' merged reconstructed plus instrumental period record. [ABSTRACT FROM AUTHOR]

Projected changes in regional seasonal precipitation due to climate change are highly uncertain, with model disagreement on even the sign of change in many regions. Using a 20-member CMIP5 ensemble under the RCP8.5 scenario, the intermodel uncertainty of the spatial patterns of projected end-of-twenty-first-century change in precipitation is found not to be strongly influenced by uncertainty in global mean temperature change. In the tropics, both the ensemble mean and intermodel uncertainty of regional precipitation change are found to be predominantly related to spatial shifts in convection and convergence, associated with processes such as sea surface temperature (SST) pattern change and land-sea thermal contrast change. The authors hypothesize that the zonal-mean seasonal migration of these shifts is driven by 1) the nonlinear spatial response of convection to SST changes and 2) a general movement of convection from land to ocean in response to SST increases. Assessment of tropical precipitation model projections over East Africa highlights the complexity of regional rainfall changes. Thermodynamically driven moisture increases determine the magnitude of the long rains (March-May) ensemble mean precipitation change in this region, whereas model uncertainty in spatial shifts of convection accounts for almost all of the intermodel uncertainty. Moderate correlations are found across models between the long rains precipitation change and patterns of SST change in the Pacific and Indian Oceans. Further analysis of the capability of models to represent present-day SST-rainfall links, and any relationship with model projections, may contribute to constraining the uncertainty in projected East Africa long rains precipitation. [ABSTRACT FROM AUTHOR]

The geographic and diurnal variability of moist convection over tropical Africa and the east Atlantic is examined using the Tropical Rainfall Measuring Mission (TRMM) satellite and related to the variability of the convective environment. The stratiform rain fraction is highest within oceanic and continental regions just north of the equator. Both regions have high column relative humidity (CRH). In both monsoon and semiarid continental regions, stratiform rain fractions are significantly higher on days when the CRH is high, which suggests a relationship between these quantities. Large convective systems with high echo tops dominate the rainfall over the Sahel. The importance of CAPE and shear to the development of these types of systems is suggested by the fact these systems are especially common on days when the CAPE and shear are unusually high. Both deep convective and stratiform conditional rain rates increase with the size and echo-top height of convective systems. According to the TRMM Precipitation Radar (PR) near-surface rain rate, the highest deep convective and stratiform conditional rain rates occur off the coast of West Africa. However, comparisons between the PR near-surface rain rate and rain rates computed from Z-R relationships from the literature suggest that deep convective conditional rain rates over the Sahel are underestimated by the TRMM precipitation algorithm. Over the Sahel, small (large) convective systems produce most of the rainfall in the afternoon (early morning). This is associated with enhanced convective rainfall in the afternoon and stratiform in the early morning. The transition from small to large convective systems as convection propagates away from topographic features is also observed. [ABSTRACT FROM AUTHOR]

Senegal is particularly vulnerable to precipitation variability. To investigate the influence of large-scale circulation on local-scale precipitation, a full spatial-statistical description of precipitation occurrence and amount for Senegal is developed. These regression-type models have been built on the basis of daily records at 137 locations and were developed in two stages: (i) a baseline model describing the expected daily occurrence probability and precipitation amount as spatial fields from monsoon onset to offset, and (ii) the inclusion of weather types defined from the NCEP-NCAR reanalysis 850-hPa winds and 925-hPa relative humidity establishing the link to the synoptic-scale atmospheric circulation. During peak phase, the resulting types appear in two main cycles that can be linked to passing African easterly waves. The models allow the investigation of the spatial response of precipitation occurrence and amount to a discrete set of preferred states of the atmospheric circulation. As such, they can be used for drought risk mapping and the downscaling of climate change projections. Necessary choices, such as filtering and scaling of the atmospheric data (as well as the number of weather types to be used), have been made on the basis of the precipitation models' performance instead of relying on external criteria. It could be demonstrated that the inclusion of the synoptic-scale weather types lead to skill on the local and daily scale. On the interannual scale, the models for precipitation occurrence and amount capture 26% and 38% of the interannual spatially averaged variability, corresponding to Pearson correlation coefficients of rO = 0.52 and ri = 0.65, respectively. [ABSTRACT FROM AUTHOR]

Outputs from climate models are the primary data source in climate change impact studies. However, their interpretation is not straightforward. In recent years, several methods have been developed in order to quantify the uncertainty in climate projections. One of the common assumptions in almost all these methods is that the climate models are independent. This study addresses the validity of this assumption for two ensembles of regional climate models (RCMs) from the Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) project based on the land cells covering Denmark. Daily precipitation indices from an ensemble of RCMs driven by the 40-yr ECMWF Re-Analysis (ERA-40) and an ensemble of the same RCMs driven by different general circulation models (GCMs) are analyzed. Two different methods are used to estimate the amount of independent information in the ensembles. These are based on different statistical properties of a measure of climate model error. Additionally, a hierarchical cluster analysis is carried out. Regardless of the method used, the effective number of RCMs is smaller than the total number of RCMs. The estimated effective number of RCMs varies depending on the method and precipitation index considered. The results also show that the main cause of interdependency in the ensemble is the use of the same RCM driven by different GCMs. This study shows that the precipitation outputs from the RCMs in the ENSEMBLES project cannot be considered independent. If the interdependency between RCMs is not taken into account, the uncertainty in the RCM simulations of current regional climate may be underestimated. This will in turn lead to an underestimation of the uncertainty in future precipitation projections. [ABSTRACT FROM AUTHOR]

This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann-Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature, with the median intensity of extreme precipitation changing in proportion with changes in global mean temperature at a rate of between 5.9% and 7.7% K−1, depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 13°S and 11°N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation. [ABSTRACT FROM AUTHOR]

Under global warming, increases in precipitation are expected at high latitudes and near major tropical convergence zones in some seasons, while decreases are expected in many subtropical and midlatitude areas in between. In many other areas there is no consensus among models on the sign of the projected change. This is often assumed to indicate that precipitation projections in these regions are highly uncertain. Here, twenty-first century precipitation projections under the Special Report on Emissions Scenarios (SRES) A1B scenario using 24 World Climate Research Programme (WCRP)/Coupled Model Intercomparison Project phase 3 (CMIP3) climate models are examined. In areas with no consensus on the sign of projected change there are extensive subregions where the projected change is 'very likely' (i.e., probability > 0.90) to be small (relative to, e.g., the size of interannual variability during the late twentieth century) or zero. The statistical significance of and interrelationships between methods used to identify model consensus on projected change in the 2007 Intergovernmental Panel on Climate Change (IPCC) report are examined, and the impact of interdependency among model projections on statistical significance is investigated. Interdependency among projections is shown to be much weaker than interdependency among simulations of climatology. The results show that there is more widespread consistency among the model projections than one might infer from the 2007 IPCC Fourth Assessment report. This discovery highlights the broader need to identify regions, variables, and phenomena that are expected to be little affected by anthropogenic climate change and to communicate this information to the wider community. This is especially important for projections of climate for the next 1-3 decades. [ABSTRACT FROM AUTHOR]

Projections of climate change effects for the System of Platja de Palma (SPdP) are derived using a novel statistical technique. Socioeconomic activities developed in this settlement are very closely linked to its climate. Any planning for socioeconomic opportunities in the mid- and long term must take into account the possible effects of climate change. To this aim, daily observed series of minimum and maximum temperatures, precipitation, relative humidity, cloud cover, and wind speed have been analyzed. For the climate projections, daily data generated by an ensemble of regional climate models (RCMs) have been used. To properly use RCM data at local scale, a quantile-quantile adjustment has been applied to the simulated regional projections. The method is based on detecting changes in the cumulative distribution functions between the recent past and successive time slices of the simulated climate and applying these, after calibration, to the recent past (observed) series. Results show an overall improvement in reproducing the present climate baseline when using calibrated series instead of raw RCM outputs, although the correction does not result in such clear improvement when dealing with very extreme rainfalls. Next, the corrected series are analyzed to quantify the climate change signal. An increase of the annual means for temperatures together with a decrease for the remaining variables is projected throughout the twenty-first century. Increases in weak and intense daily rainfalls and in high extremes for daily maximum temperature can also be expected. With this information at hand, the experts planning the future of SPdP can respond more effectively to the problem of local adaptation to climate change. [ABSTRACT FROM AUTHOR]

This is the second of a two-part investigation of rainfall in southern Africa during the strong El Niño of 1997/98. In Part I it was shown that widespread drought in southern Africa, typical of past El Niño events occurring between 1950 and 2000, generally failed to materialize during the 1997/98 El Niño, most notably during January–March (JFM) 1998. Here output from three atmospheric general circulation models (AGCMs) forced with observed sea surface temperatures (SSTs) and seasonal forecasts from three coupled models are examined to see to what extent conditions in JFM 1998 could have potentially been anticipated. All three AGCMs generated widespread drought conditions across southern Africa, similar to those during past El Niño events, and did a generally poor job in generating the observed rainfall and atmospheric circulation anomaly patterns, particularly over the eastern and southern Indian Ocean. In contrast, two of the three coupled models showed a higher probability of wetter conditions in JFM 1998 than for past El Niño events, with an enhanced moisture flux from the Indian Ocean, as was observed. However, neither the AGCMs nor the coupled models generated anomalous stationary wave patterns consistent with observations over the South Atlantic and Pacific. The failure of any of the models to reproduce an enhanced Angola low (favoring rainfall) associated with an anomalous wave train in this region suggests that the coupled models that did indicate wetter conditions in JFM 1998 compared to previous El Niño episodes may have done so, at least partially, for the wrong reasons. The general inability of the climate models used in this study to generate key features of the seasonal climate over southern Africa in JFM 1998 suggests that internal atmospheric variability contributed to the observed rainfall and circulation patterns that year. With the caveat that current climate models may not properly respond to SST boundary forcing important to simulating southern Africa climate, this study finds that the JFM 1998 rainfall in southern Africa may have been largely unpredictable on seasonal time scales. [ABSTRACT FROM AUTHOR]

The global monsoon climate variability during the second half of the twentieth century simulated by 21 coupled global climate models (CGCMs) that participated in the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 (CMIP3) is evaluated. Emphasis was placed on climatology, multidecadal trend, and the response of the global monsoon precipitation to volcanic aerosols. The impact of the atmospheric model’s horizontal resolution on the group ensemble mean (GEM; obtained from the three resolution groups) simulations of global monsoon climate is also examined. The CMIP3 CGCMs’ multimodel ensemble simulates a reasonably realistic climatology of the global monsoon precipitation and circulation. The GEMs are also able to capture the gross features of the global monsoon precipitation and westerly domains. However, the spreading among the rainfall GEMs is large, particularly at the windward side of narrow mountains (e.g., the western coast of India, the Philippines, Mexico, and the steep slope of the Tibetan Plateau). Main common biases in modeling rainfall climatology include a northeastward shift of the intertropical convergence zone (ITCZ) in the tropical North Pacific and a southward migration of the North Atlantic ITCZ during boreal winter. The trend in the Northern Hemisphere land monsoon index (NHMI) detected in the CMIP3 models is generally consistent with the observations, albeit with much weaker magnitude. The significant decreasing NHMI trend during 1951–85 and 1951–99 occurs mainly in the models with volcanic aerosols (VOL models). This volcanic signal is detectable by comparison of the forced and free runs. It is estimated that from about one-quarter to one-third of the drying trend in the Northern Hemisphere land monsoon precipitation over the latter half of the twentieth century was likely due to the effects of the external volcanic forcings. On the other hand, the significant increasing trend in the global ocean monsoon index (GOMI) during 1980–99 appears chiefly in those models that are free of volcanic aerosols (No-VOL models). The exclusion of the volcanic aerosols is significant in simulating the positive GOMI trend against the internal variability of each model. These results suggest the climatic importance of the volcanic forcings in the global monsoon precipitation variability. [ABSTRACT FROM AUTHOR]

A revised framework is presented that quantifies observed changes in the climate of the contiguous United States through analysis of a revised version of the U.S. Climate Extremes Index (CEI). The CEI is based on a set of climate extremes indicators that measure the fraction of the area of the United States experiencing extremes in monthly mean surface temperature, daily precipitation, and drought (or moisture surplus). In the revised CEI, auxiliary station data, including recently digitized pre-1948 data, are incorporated to extend it further back in time and to improve spatial coverage. The revised CEI is updated for the period from 1910 to the present in near–real time and is calculated for eight separate seasons, or periods. Results for the annual revised CEI are similar to those from the original CEI. Observations over the past decade continue to support the finding that the area experiencing much above-normal maximum and minimum temperatures in recent years has been on the rise, with infrequent occurrence of much below- normal mean maximum and minimum temperatures. Conversely, extremes in much below-normal mean maximum and minimum temperatures indicate a decline from about 1910 to 1930. An increasing trend in the area experiencing much above-normal proportion of heavy daily precipitation is observed from about 1950 to the present. A period with a much greater-than-normal number of days without precipitation is also noted from about 1910 to the mid-1930s. Warm extremes in mean maximum and minimum temperature observed during the summer and warm seasons show a more pronounced increasing trend since the mid-1970s. Results from the winter season show large variability in extremes and little evidence of a trend. The cold season CEI indicates an increase in extremes since the early 1970s yet has large multidecadal variability. [ABSTRACT FROM AUTHOR]

In this study, the spatial and temporal distribution of precipitation in the broader Greek area is investigated for the 26-yr period 1979–2004 by using monthly mean satellite-based data, with complete spatial coverage, taken from the Global Precipitation Climatology Project (GPCP). The results show that there exists a clear contrast between the more rainy western Greek area (rainside) and the drier eastern one (rainshadow), whereas there is little precipitation over the islands, particularly in the southern parts. The computed long-term areal mean annual precipitation amount averaged for the study area is equal to P = 639.8 ± 44.8 mm yr-1, showing a decreasing trend of -2.32 mm yr-1 or -60.3 mm over the 26-yr study period, which corresponds to -9.4%. This decrease of precipitation, arising primarily in winter and secondarily in spring, is the result of a decreasing trend from 1979 through the 1980s, against an increase during the 1990s through the early 2000s, followed again by a decrease up to the year 2004. The performed analysis reveals an increasing trend of precipitation in the central and northern parts of the study region, contrary to an identified decreasing trend in the southern parts, which is indicative of threatening desertification processes in those areas in the context of climatic changes in the climatically sensitive Mediterranean basin. In addition, the analysis shows that the precipitation decrease is due to a corresponding decrease of maximum precipitation against rather unchanged minimum precipitation amounts. The analysis indicates that the changing precipitation patterns in the region during winter are significantly anticorrelated with the North Atlantic Oscillation (NAO) index values, against a positive correlation during summer, highlighting thus the role of large-scale circulation patterns for regional climates. The GPCP precipitation data are satisfactorily correlated with instrumental measurements from 36 stations uniformly distributed over the study area (correlation coefficient R = 0.74 for all stations; R = 0.63–0.91 for individual stations). [ABSTRACT FROM AUTHOR]

Interannual extremes in New Zealand rainfall and their modulation by modes of Southern Hemisphere climate variability are examined in observations and a coupled climate model. North Island extreme dry (wet) years are characterized by locally increased (reduced) sea level pressure (SLP), cold (warm) sea surface temperature (SST) anomalies in the southern Tasman Sea and to the north of the island, and coinciding reduced (enhanced) evaporation upstream of the mean southwesterly airflow. During extreme dry (wet) years in South Island precipitation, an enhanced (reduced) meridional SLP gradient occurs, with circumpolar strengthened (weakened) subpolar westerlies and an easterly (westerly) anomaly in zonal wind in the subtropics. As a result, via Ekman transport, anomalously cold (warm) SST appears under the subpolar westerlies, while anomalies of the opposite sign occur farther north. The phase and magnitude of the resulting SST and evaporation anomalies cannot account for the rainfall extremes over the South Island, suggesting a purely atmospheric mode of variability as the driving factor, in this case the Southern Annular Mode (SAM). New Zealand rainfall variability is predominantly modulated by two Southern Hemisphere climate modes, namely, the El Niño–Southern Oscillation (ENSO) and the SAM, with a latitudinal gradation in influence of the respective phenomena, and a notable interaction with orographic features. While this heterogeneity is apparent both latitudinally and as a result of orographic effects, climate modes can force local rainfall anomalies with considerable variations across both islands. North Island precipitation is for the most part regulated by both local air–sea heat fluxes and circulation changes associated with the tropical ENSO mode. In contrast, for the South Island the influence of the large-scale general atmospheric circulation dominates, especially via the strength and position of the subpolar westerlies, which are modulated by the extratropical SAM. [ABSTRACT FROM AUTHOR]

This study examines the spatial coherence characteristics of daily station observations of rainfall in five tropical regions during the principal rainfall season(s): the Brazilian Nordeste, Senegal, Kenya, northwestern India, and northern Queensland. The rainfall networks include between 9 and 81 stations, and 29–70 seasons of observations. Seasonal-mean rainfall totals are decomposed in terms of daily rainfall frequency (i.e., the number of wet days) and mean intensity (i.e., the mean rainfall amount on wet days). Despite the diverse spatiotemporal sampling, orography, and land cover between regions, three general results emerge. 1) Interannual anomalies of rainfall frequency are usually the most spatially coherent variable, generally followed closely by the seasonal amount, with the daily mean intensity in a distant third place. In some cases, such as northwestern India, which is characterized by large daily rainfall amounts, the frequency of occurrence is much more coherent than the seasonal amount. 2) On daily time scales, the interstation correlations between amounts on wet days always fall to insignificant values beyond a distance of about 100 km. The spatial scale of daily rainfall occurrence is larger and more variable among the networks. 3) The regional-scale signal of the seasonal amount is primarily related to a systematic spatially coherent modulation of the frequency of occurrence. [ABSTRACT FROM AUTHOR]

Daily precipitation data from climate change simulations using the latest generation of coupled climate system models are analyzed for potential future changes in precipitation characteristics. For the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) B1 (a low projection), A1B (a medium projection), and A2 (a high projection) during the twenty-first century, all the models consistently show a shift toward more intense and extreme precipitation for the globe as a whole and over various regions. For both SRES B1 and A2, most models show decreased daily precipitation frequency and all the models show increased daily precipitation intensity. The multimodel averaged percentage increase in the precipitation intensity (2.0% K-1) is larger than the magnitude of the precipitation frequency decrease (-0.7% K-1). However, the shift in precipitation frequency distribution toward extremes results in large increases in very heavy precipitation events (>50 mm day-1), so that for very heavy precipitation, the percentage increase in frequency is much larger than the increase in intensity (31.2% versus 2.4%). The climate model projected increases in daily precipitation intensity are, however, smaller than that based on simple thermodynamics (∼7% K-1). Multimodel ensemble means show that precipitation amount increases during the twenty-first century over high latitudes, as well as over currently wet regions in low- and midlatitudes more than other regions. This increase mostly results from a combination of increased frequency and intensity. Over the dry regions in the subtropics, the precipitation amount generally declines because of decreases in both frequency and intensity. This indicates that wet regions may get wetter and dry regions may become drier mostly because of a simultaneous increase (decrease) of precipitation frequency and intensity. [ABSTRACT FROM AUTHOR]

Summer simulations over the contiguous United States and Mexico with the Regional Atmospheric Modeling System (RAMS) dynamically downscaling the NCEP–NCAR Reanalysis I for the period 1950–2002 (described in Part I of the study) are evaluated with respect to the three dominant modes of global SST. Two of these modes are associated with the statistically significant, naturally occurring interannual and interdecadal variability in the Pacific. The remaining mode corresponds to the recent warming of tropical sea surface temperatures. Time-evolving teleconnections associated with Pacific SSTs delay or accelerate the evolution of the North American monsoon. At the period of maximum teleconnectivity in late June and early July, there is an opposite relationship between precipitation in the core monsoon region and the central United States. Use of a regional climate model (RCM) is essential to capture this variability because of its representation of the diurnal cycle of convective rainfall. The RCM also captures the observed long-term changes in Mexican summer rainfall and suggests that these changes are due in part to the recent increase in eastern Pacific SST off the Mexican coast. To establish the physical linkage to remote SST forcing, additional RAMS seasonal weather prediction mode simulations were performed and these results are briefly discussed. In order for RCMs to be successful in a seasonal weather prediction mode for the summer season, it is required that the GCM provide a reasonable representation of the teleconnections and have a climatology that is comparable to a global atmospheric reanalysis. [ABSTRACT FROM AUTHOR]

Studying the role of land surface conditions in the Mexican portion of the North American monsoon system (NAMS) region has been a challenge due to the paucity of long-term observations. A long-term gridded observation-based climate dataset suitable for forcing land surface models, as well as model-derived land surface states and fluxes for a domain consisting of all of Mexico, is described. The datasets span the period of January 1925–October 2004 at 1/8° spatial resolution at a subdaily (3 h) time step. The simulated runoff matches the observations plausibly over most of the 14 small river basins spanning all of Mexico, which suggests that long-term mean evapotranspiration is realistically reproduced. On this basis, and given the physically based model parameterizations of soil moisture and energy fluxes, the other surface fluxes and state variables such as soil moisture should be represented reasonably. In addition, a comparison of the surface fluxes from this study is performed with North American Regional Reanalysis (NARR) data on a seasonal mean basis. The results indicate that downward shortwave radiation is generally smaller than in the NARR data, especially in summer. Net radiation, on the other hand, is somewhat larger in the Variable Infiltration Capacity (VIC) hydrological model than in the NARR data for much of the year over much of the domain. The differences in radiative and turbulent fluxes are attributed to (i) the parameterization used in the VIC forcings for solar and downward longwave radiation, which links them to the daily temperature and temperature range, and (ii) differences in the land surface parameterizations used in VIC and the NCEP–Oregon State University–U.S. Air Force–NWS/Hydrologic Research Lab (Noah) land scheme used in NARR. [ABSTRACT FROM AUTHOR]

Precipitation variability is analyzed in two versions of the Community Atmospheric Model (CAM), the standard model, CAM, and a “multiscale modeling framework” (MMF), in which the cumulus parameterization has been replaced with a cloud-resolving model. Probability distribution functions (PDFs) of daily mean rainfall in three geographic locations [the Amazon Basin and western Pacific in December–February (DJF) and the North American Great Plains in June–August (JJA)] indicate that the CAM produces too much light–moderate rainfall (10 ∼ 20 mm day-1), and not enough heavy rainfall, compared to observations. The MMF underestimates rain contributions from the lightest rainfall rates but correctly simulates more intense rainfall events. These differences are not always apparent in seasonal mean rainfall totals. Analysis of 3–6-hourly rainfall and sounding data in the same locations reveals that the CAM produces moderately intense rainfall as soon as the boundary layer energizes. Precipitation is also concurrent with tropospheric relative humidity and lifted parcel buoyancy increases. In contrast, the MMF and observations are characterized by a lag of several hours between boundary layer energy buildup and precipitation, and a gradual increase in the depth of low-level relative humidity maximum prior to rainfall. The environmental entrainment rate selection in the CAM cumulus parameterization influences CAM precipitation timing and intensity, and may contribute to the midlevel dry bias in that model. The resulting low-intensity rainfall in the CAM leads to rainfall–canopy vegetation interactions that are different from those simulated by the MMF. The authors present evidence suggesting that this interaction may artificially inflate North American Great Plains summertime rainfall totals in the CAM. [ABSTRACT FROM AUTHOR]

The water resources of the western United States depend heavily on snowpack to store part of the wintertime precipitation into the drier summer months. A well-documented shift toward earlier runoff in recent decades has been attributed to 1) more precipitation falling as rain instead of snow and 2) earlier snowmelt. The present study addresses the former, documenting a regional trend toward smaller ratios of winter-total snowfall water equivalent (SFE) to winter-total precipitation (P) during the period 1949–2004. The trends toward reduced SFE are a response to warming across the region, with the most significant reductions occurring where winter wet-day minimum temperatures, averaged over the study period, were warmer than -5°C. Most SFE reductions were associated with winter wet-day temperature increases between 0° and +3°C over the study period. Warmings larger than this occurred mainly at sites where the mean temperatures were cool enough that the precipitation form was less susceptible to warming trends. The trends toward reduced SFE/P ratios were most pronounced in March regionwide and in January near the West Coast, corresponding to widespread warming in these months. While mean temperatures in March were sufficiently high to allow the warming trend to produce SFE/P declines across the study region, mean January temperatures were cooler, with the result that January SFE/P impacts were restricted to the lower elevations near the West Coast. Extending the analysis back to 1920 shows that although the trends presented here may be partially attributable to interdecadal climate variability associated with the Pacific decadal oscillation, they also appear to result from still longer-term climate shifts. [ABSTRACT FROM AUTHOR]

Late spring (21 April–20 May) precipitation to the south of the Yangtze River in China along the East Asian front is a salient feature of the global climate. The present analysis reveals that during 1958–2000 South China (26°–31°N, 110°–122°E) has undergone a significant decrease in late spring precipitation since the late 1970s. The sudden reduction of the precipitation concurs with a notable cooling in the upper troposphere over the central China (30°–40°N, 95°–125°E). The upper-level cooling is associated with an anomalous meridional cell with descending motions in the latitudes 26°–35°N and low-level northerly winds over southeastern China (22°–30°N, 110°–125°E), causing deficient rainfall over South China. The late spring cooling in the upper troposphere over the central China is found to strongly link to the North Atlantic Oscillation (NAO) in the preceding winter. During winters with a positive NAO index, the upper-tropospheric cooling occurs first to the north of the Tibetan Plateau in early–middle spring, then propagates southeastward to central China in late spring. It is suggested that the interdecadal change of the winter NAO is the root cause for the late spring drought over South China in recent decades. [ABSTRACT FROM AUTHOR]

Interannual variability of warm-season rainfall over the Great Plains is analyzed using the recently released North American Regional Reanalysis (NARR). The new dataset differs from its global counterparts in the additional assimilation of precipitation and radiances. This along with the use of a more comprehensive land surface model in generation of NARR offers the prospect of obtaining improved estimates of surface hydrologic and near-surface meteorological fields. NARR’s representation of hydroclimate is used to weigh in on the authors’ recent finding of the dominance of large-scale moisture flux convergence over evaporation in accounting for Great Plains precipitation variations. Evaporation estimates are notoriously uncertain and, while the NARR ones are not assured to be realistic, they are more constrained than those diagnosed before from inline and offline assessments. NARR’s portrayal of warm-season hydroclimate variability corroborates the importance of remote water sources in generation of Great Plains precipitation variability and supports the authors’ claim that some state-of-the-art atmosphere/land surface models vigorously recycle precipitation, erroneously, at least in context of Great Plains interannual variability. These very models have been key to recent claims of strong coupling between soil moisture and precipitation. [ABSTRACT FROM AUTHOR]

The climate simulated by a global atmosphere–land model with a physically based subgrid orography scheme is evaluated in 10 selected regions. Climate variables simulated for each of multiple elevation classes within each grid cell are mapped according to a high-resolution distribution of surface elevation in each region. Comparison of the simulated annual mean climate with gridded observations leads to the following conclusions. At low to moderate elevations the downscaling scheme correctly simulates increasing precipitation, decreasing temperature, and increasing snow with increasing elevation across distances smaller than 100 km. At high elevations the downscaling scheme correctly simulates decreasing precipitation with increasing elevation. The rain shadow of many mountain ranges is poorly resolved, with too little precipitation simulated on the windward side of mountain ranges and too much on the lee side. The simulated sensitivity of surface air temperature to surface elevation is too strong, particularly in valleys influenced by drainage circulations. Observations show little evidence of a “snow shadow,” so the neglect of the subgrid rain shadow does not produce an unrealistic simulation of the snow distribution. Summertime snow area, which is a proxy for land ice, is much larger than observed, mostly because of excessive snowfall but in some places because of a cold bias. Summertime snow water equivalent is far less than the observed thickness of glaciers because a 1-m upper bound on snow water is applied to the simulations and because snow transport by slides is neglected. The 1-m upper bound on snow water equivalent also causes an underestimate of seasonal snow water during late winter, compared with gridded station measurements. Potential solutions to these problems are discussed. [ABSTRACT FROM AUTHOR]

A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America. [ABSTRACT FROM AUTHOR]