Which downscaled rainfall data for climate change impact studies in urban areas? Review of current approaches and trends

Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern.     

A Europe–South America network for climate change assessment and impact studies

The goal of the CLARIS project was to build an integrated European–South American network dedicated to promote common research strategies to observe and predict climate changes and their consequent socio-economic impacts taking into account the climate and societal peculiarities of South America. Reaching that goal placed the present network as a privileged advisor to contribute to the design of adaptation strategies in a region strongly affected by and dependent on climate variability (e.g. agriculture, health, hydro-electricity). Building the CLARIS network required fulfilling the following three objectives: (1) The first objective of CLARIS was to set up and favour the technical transfer and expertise in earth system and regional climate modelling between Europe and South America together with the providing of a list of climate data (observed and simulated) required for model validations; (2) The second objective of CLARIS was to facilitate the exchange of observed and simulated climate data between the climate research groups and to create a South American high-quality climate database for studies in extreme events and long-term climate trends; (3) Finally, the third objective of CLARIS was to strengthen the communication between climate researchers and stakeholders, and to demonstrate the feasibility of using climate information in the decision-making process.     

A scaling analysis of soil moisture–precipitation interactions in a regional climate model

The University of Oklahoma’s Advanced Regional Prediction System (ARPS) was used to examine the impacts of varying mean soil moisture and model resolution on the magnitude and frequency of precipitation events in the U.S. Central Plains and to determine whether modeled soil moisture and precipitation fields exhibit scale invariance using the statistical moments. It was found that high soil moisture resulted in greater precipitation amounts and a higher frequency of events, suggesting the occurrence of a positive soil moisture–precipitation feedback. The scaling analysis performed on cumulative precipitation determined that these fields did not exhibit signs of self-similarity and, therefore, statistical properties cannot be predicted at other resolutions. The scaling properties of soil moisture were highly variable in time which has important implications for the use of remotely sensed data, as scaling properties from 1 day cannot necessarily be applied to subsequent days.     

Historical and potential changes of precipitation and temperature of Alberta subjected to climate change impact: 1900–2100

We investigated changes to precipitation and temperature of Alberta for historical and future periods. First, the Mann-Kendall test and Sen’s slope were used to test for historical trends and trend magnitudes from the climate data of Alberta, respectively. Second, the Special Report on Emissions Scenarios (SRES) (A1B, A2, and B1) of CMIP3 (Phase 3 of Coupled Model Intercomparison Project), projected by seven general circulation models (GCM) of the Intergovernmental Panel on Climate Change (IPCC) for three 30 years periods (2020s, 2050s, and 2080s), were used to evaluate the potential impact of climate change on precipitation and temperature of Alberta. Third, trends of projected precipitation and temperature were investigated, and differences between historical versus projected trends were estimated. Using the 50-km resolution dataset from CANGRD (Canadian Grid Climate Data), we found that Alberta had become warmer and somewhat drier for the past 112 years (1900–2011), especially in central and southern Alberta. For observed precipitation, upward trends mainly occurred in northern Alberta and at the leeward side of Canadian Rocky Mountains. However, only about 13 to 22 % of observed precipitation showed statistically significant increasing trends at 5 % significant level. Most observed temperature showed significant increasing trends, up to 0.05 °C/year in DJF (December, January, and February) in northern Alberta. GCMs’ SRES projections indicated that seasonal precipitation of Alberta could change from ?25 to 36 %, while the temperature would increase from 2020s to 2080s, with the largest increase (6.8 °C) in DJF. In all 21 GCM-SRES cases considered, precipitation in both DJF and MAM (March, April, and May) is projected to increase, while temperature is consistently projected to increase in all seasons, which generally agree with the trends of historical precipitation and temperature. The SRES A1B scenario of CCSM3 might project more realistic future climate for Alberta, where its water resources can become more critical in the future as its streamflow is projected to decrease continually in the future.     

Potential impact of climate change on carbon in agricultural soils in Canada 2000–2099

Under the threat of global warming it is important to determine the impact that future changes in climate may have on the environment and to what extent any adverse effects can be mitigated. In this study we assessed the impact that climate change scenarios may have on soil carbon stocks in Canada and examined the potential for agricultural management practices to improve or maintain soil quality. Historical weather data from 1951 to 2001 indicated that semi-arid soils in western Canada have become warmer and dryer and air temperatures have increased during the spring and winter months. Results from the Canadian Center for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model (CGCM1,2) under two climate change forcing scenarios also indicated that future temperatures would increase more in the spring and winter. Precipitation increased significantly under the IPCC IS92a scenario and agreed with historical trends in eastern Canada whereas the IPCC SRES B2 scenario indicated very little change in precipitation and better matched historical trends in western Canada. The Century model was used to examine the influence of climate change on agricultural soil carbon (C) stocks in Canada. Relative to simulations using historical weather data, model results under the SRES B2 climate scenario indicated that agricultural soils would lose 160 Tg of carbon by 2099 and under the IS92a scenario would lose 53 Tg C. Carbon was still lost from soils in humid climatic regions even though C inputs from crops increased by 10–13%. Carbon factors associated with changes in management practices were also estimated under both climate change scenarios. There was little difference in factors associated with conversion from conventional to no-till agriculture, while carbon factors associated with the conversion of annual crops to perennial grass were lower than for historical data in semi-arid soils because water stress hampered crop production but were higher in humid soils.     

Observed (1970–1999) climate variability in Central America using a high-resolution meteorological dataset with implication to climate change studies

High spatial resolution of precipitation (P) and average air temperature (Tavg) datasets are ideal for determining the spatial patterns associated with large-scale atmospheric and oceanic indexes, and climate change and variability studies, however such datasets are not usually available. Those datasets are particularly important for Central America because they allow the conception of climate variability and climate change studies in a region of high climatic heterogeneity and at the same time aid the decisionmaking process at the local scale (municipalities and districts). Tavg data from stations and complementary gridded datasets at 50 km resolution were used to generate a high-resolution (5 km grid) dataset for Central America from 1970 to 1999. A highresolution P dataset was used along with the new Tavg dataset to study climate variability and a climate change application. Consistently with other studies, it was found that the 1970-1999 trends in P are generally non-significant, with the exception of a few small locations. In the case of Tavg, there were significant warming trends in most of Central America, and cooling trends in Honduras and northern Panama. When the sea surface temperature anomalies between the Tropical Pacific and the Tropical Atlantic have different (same) sign, they are a good indicator of the sign of P (Tavg) annual anomalies. Even with non-significant trends in precipitation, the significant warming trends in Tavg in most of Central America can have severe consequences in the hydrology and water availability of the region, as the warming would bring increases in evapotranspiration, drier soils and higher aridity.     

Does increasing the spatial resolution of a regional climate model improve the simulated daily precipitation?

Three different resolution (50, 12, and 1.5 km) regional climate model simulations are compared in terms of their ability to simulate moderate and high daily precipitation events over the southern United Kingdom. The convection-permitting 1.5-km simulation is carried out without convective parametrisation. As in previous studies, increasing resolution (especially from 50 to 12 km) is found to improve the representation of orographic precipitation. The 50-km simulation underestimates mean precipitation over the mountainous region of Wales, and event intensity tends to be too weak; this bias is reduced in both the 12- and 1.5-km simulations for both summer and winter. In south–east England lowlands where summer extremes are mostly convective, increasing resolution does not necessary lead to an improvement in the simulation. For the 12-km simulation, simulated daily extreme events are overly intense. Even though the average intensity of summer daily extremes is improved in the 1.5-km simulation, this simulation has a poorer mean bias with too many events exceeding high thresholds. Spatial density and clustering of summer extremes in south–east England are poorly simulated in both the 12- and 1.5-km simulations. In general, we have not found any clear evidence to show that the 1.5-km simulation is superior to the 12-km simulation, or vice versa at the daily level.     

Recent (1980–2009) evidence of climate change in the upper Karakoram, Pakistan

We investigate here recent (1980–2009) climate variability in the upper Karakoram, Northern Pakistan, of particular interest given the peculiar glacier behavior during the last two decades. Differently from other glacierized regions in the Hindu Kush–Karakoram–Himalaya region, glaciers in the Karakoram display limited ice thinning, and in some cases advancing has been detected. Climate analysis is required to describe recent (i.e., last three decades) variability, to aid highlighting of the factors driving glacier evolution. Starting from monthly data, we analyze seasonal values of total precipitation, number of wet days, maximum (max) and minimum (min) air temperature, max precipitation in 24 h, and cloud cover for 17 weather stations in the upper Karakoram, clustered within three climatic regions as per use of principal components analysis. We detect possible nonstationarity in each of these regions by way of (1) linear regression, (2) moving window average, and (3) Mann–Kendall test, also in progressive form, to detect the onset date of possible trends. We then evaluate linear correlation coefficients between Northern Atlantic Oscillation (NAO) index and climate variables to assess effectiveness of teleconnections, claimed recently to affect climate in this area. Also, we compare temperature within the investigated zone against global temperature anomalies, to evidence enhanced warming within this area. We found mostly nonsignificant changes of total precipitation, unless for few stations displaying increase in Chitral-Hindu Kush region and Northwest Karakoram, or Gilgit area, and decrease in Western Himalaya, Kotli region. Max precipitation is mostly unchanged, unless for slight increase in Chitral and Gilgit areas, and slight decrease in Kotli region. Number of wet days is mostly increasing in Gilgit area, and decreasing in Chitral area, with no clear signal in Kotli region. Min temperatures increase always but during Summer, when decreasing values are detected, especially for Gilgit and Chitral regions. Max temperatures are found to increase everywhere. Cloud cover is significantly increasing in Gilgit area, but decreasing otherwise, especially in Kotli region. Max temperature regime is significantly positively correlated against global thermal anomaly, while min temperature regime is nonsignificantly negatively correlated. Max and min temperatures seem mostly negatively correlated to NAO. Some dependence of trend intensity for the considered variables against altitude is found, different for each region, suggesting that investigation of weather variables at the highest altitudes is warranted to discriminate further climate variability in the area.     

Radial growth change of temperate tree species in response to altered regional climate and air quality in the period 1901–2008

Both increasing and decreasing 20th century growth trends have been reported in forests throughout Europe, but only for few species and areas suitable modelling techniques have been used to distinguish individual tree growth (operating on a local scale) from growth change due to exogenous factors (operating on a broad geographical scale). This study relates for the first time observed growth changes, in terms of basal area increment (BAI) of dominant trees of pedunculate oak, common beech and Scots pine, in north-west European temperate lowland forests (Flanders) to climate, atmospheric CO₂ and tropospheric O₃ concentrations, N deposition, site quality and forest structure for more than a century (the period 1901?C2008), applying mixed models. Growth change during the 20th century is observed for oak (increasing growth) and beech (increasing growth until the 1960s, growth decline afterwards), but not for pine. It was possible to relate growth change of oak and beech to climate time series and N deposition trends. Adding time series for CO₂ and O₃ concentration did not significantly improve model results. For oak and beech a switch from positive to negative growth response with increasing nitrogen deposition throughout time is observed. Growth increase for oak is mainly determined by the interaction between growing season temperature and soil water recharge. It is reasonable to assume that the observed growth trend for oak will continue for as long as early season water availability is not compromised. The decreasing trend in summer relative air humidity observed since the 1960s in the study area can be a main cause of recent beech BAI decrease. A further growth decline of beech can be expected, independent of site quality.     

An atmosphere–ocean regional climate model for the Mediterranean area: assessment of a present climate simulation

We present an atmosphere–ocean regional climate model for the Mediterranean basin, called the PROTHEUS system, composed by the regional climate model RegCM3 as the atmospheric component and by a regional configuration of the MITgcm model as the oceanic component. The model is applied to an area encompassing the Mediterranean Sea and compared to a stand-alone version of its atmospheric component. An assessment of the model performances is done by using available observational datasets. Despite a persistent bias, the PROTHEUS system is able to capture the inter-annual variability of seasonal sea surface temperature (SST) and also the fine scale spatio-temporal evolution of observed SST anomalies, with spatial correlation as high as 0.7 during summer. The close inspection of a 10-day strong wind event during the summer of 2000 proves the capability of the PROTHEUS system to correctly describe the daily evolution of SST under strong air–sea interaction conditions. As a consequence of the model’s skill in reproducing observed SST and wind fields, we expect a reliable estimation of air–sea fluxes. The model skill in reproducing climatological land surface fields is in line with that of state of the art regional climate models.     

High impact,low probability? An empirical analysis of risk in the economics of climate change

To what extent does economic analysis of climate change depend on low-probability, high-impact events? This question has received a great deal of attention lately, with the contention increasingly made that climate damage could be so large that societal willingness to pay to avoid extreme outcomes should overwhelm other seemingly important assumptions, notably on time preference. This paper provides an empirical examination of some key theoretical points, using a probabilistic integrated assessment model. New, fat-tailed distributions are inputted for key parameters representing climate sensitivity and economic costs. It is found that welfare estimates do strongly depend on tail risks, but for a set of plausible assumptions time preference can still matter.     

Trends in precipitation parameters in the climate zones of southern Russia (1961–2011)

The data of 19 weather stations for 1961-2011 on total and maximum daily precipitation for the plain (<500 m above the sea level), foothill (500-1000 m), and mountain (1000-2000 m) zones of the south of European Russia are used for analyzing the precipitation regime, investigating its trends, revealing the extremes, and making conclusions on zonal seasonal and annual variations in precipitation.     

Analysis of extreme precipitation characteristics in low mountain areas based on three-dimensional copulas—taking Kuandian County as an example

Rainfall in New South Wales (NSW), located in the southeast of the Australian continent, is known to be influenced by four major climate drivers: the El Niño/Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD). Many studies have shown the influences of ENSO, IPO modulation, SAM and IOD on rainfall in Australia and on southeast Australia in particular. However, only limited work has been undertaken using a multiple regression framework to examine the extent of the combined effect of these climate drivers on rainfall. This paper analysed the role of these combined climate drivers and their interaction on the rainfall in NSW using Bayesian Model Averaging (BMA) to account for model uncertainty by considering each of the linear models across the whole model space which is equal to the set of all possible combinations of predictors to find the model posterior probabilities and their expected predictor coefficients. Using BMA for linear regression models, we are able to corroborate and confirm the results from many previous studies. In addition, the method gives the ranking order of importance and the probability of the association of each of the climate drivers and their interaction on the rainfall at a site. The ability to quantify the relative contribution of the climate drivers offers the key to understand the complex interaction of drivers on rainfall, or lack of rainfall in a region, such as the three big droughts in southeastern Australia which have been the subject of discussion and debate recently on their causes.     

Regional mean and variability characteristics of temperature and precipitation over Thailand in 1961–2000 by a regional climate model and their evaluation

This study presents the characterization of regional means and variability of temperature and precipitation in 1961–2000 for Thailand using regional climate model RegCM3. Two fine-resolution (20 km) simulations forced by ERA-40 reanalysis data were performed, with the default land covers and with a land-cover modification strategy suggested by a previous work. The strategy was shown to substantially alleviate the problem of systematic underestimation of temperature given by the default simulation, for most part of Thailand in both dry and wet seasons. The degree of bias in precipitation tends to vary differently in every sub-region and season considered. The patterns of seasonal variation of both climatic variables are acceptably reproduced. Simulated 850-hPa winds have general agreement with those of ERA-40, but wind speed is overestimated over the Gulf of Thailand during the dry months, potentially bringing excessive moisture to and causing more rain than actual in the south. Long-term trends in temperature are reasonably predicted by the model while those in observed and simulated precipitations for upper Thailand are in the opposite directions. Apart from the conventional methods used in characterization, spectral decomposition using Kolmogorov–Zurbenko filters was applied to inspect the model’s capability of accounting for variability (here, in terms of variance) in both climatic variables on three temporal scales (short term, seasonal, and long term). The model was found to closely estimate the total variances in the original time series and fairly predict the relative variance contributions on all temporal scales. The latter finding is in line with the results from an additional spectral coherence analysis. Overall, the model was shown to be acceptably adequate for use in support of further climate studies for Thailand, and its evident strength is the capability of reproducing seasonal characteristics and, to a lesser degree, trends.     

Validation of precipitation over Japan during 1985–2004 simulated by three regional climate models and two multi-model ensemble means

We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate.     

Development of regional future climate change scenarios in South America using the Eta CPTEC/HadCM3 climate change projections: climatology and regional analyses for the Amazon, S?o Francisco and the Paraná River basins

The objective of this study is to assess the climate projections over South America using the Eta-CPTEC regional model driven by four members of an ensemble of the Met Office Hadley Centre Global Coupled climate model HadCM3. The global model ensemble was run over the twenty-first century according to the SRES A1B emissions scenario, but with each member having a different climate sensitivity. The four members selected to drive the Eta-CPTEC model span the sensitivity range in the global model ensemble. The Eta-CPTEC model nested in these lateral boundary conditions was configured with a 40-km grid size and was run over 1961–1990 to represent baseline climate, and 2011–2100 to simulate possible future changes. Results presented here focus on austral summer and winter climate of 2011–2040, 2041–2070 and 2071–2100 periods, for South America and for three major river basins in Brazil. Projections of changes in upper and low-level circulation and the mean sea level pressure (SLP) fields simulate a pattern of weakening of the tropical circulation and strengthening of the subtropical circulation, marked by intensification at the surface of the Chaco Low and the subtropical highs. Strong warming (4–6°C) of continental South America increases the temperature gradient between continental South America and the South Atlantic. This leads to stronger SLP gradients between continent and oceans, and to changes in moisture transport and rainfall. Large rainfall reductions are simulated in Amazonia and Northeast Brazil (reaching up to 40%), and rainfall increases around the northern coast of Peru and Ecuador and in southeastern South America, reaching up to 30% in northern Argentina. All changes are more intense after 2040. The Precipitation–Evaporation (P–E) difference in the A1B downscaled scenario suggest water deficits and river runoff reductions in the eastern Amazon and S?o Francisco Basin, making these regions susceptible to drier conditions and droughts in the future.     

Mean, interannual variability and trends in a regional climate change experiment over Europe. I. Present-day climate (1961–1990)

We present an analysis of a multidecadal simulation of present-day climate (1961–1990) over Europe with the regional climate model RegCM nested within the global atmospheric model HadAMH. Climatic means, interannual variability and trends are examined, with focus on surface air temperature and precipitation. The RegCM driven by HadAMH fields is able to reproduce the basic features of the observed mean surface climate over Europe, its seasonal evolution and the regional detail due to topographic forcing. Surface air temperature biases are mostly less than 1–2 °C and precipitation biases mostly within 10–20%. The RegCM has more intense vertical transport of temperature and water vapor than HadAMH, which results in lower surface air temperatures and greater precipitation than found in the HadAMH simulation. In some cases this is in the direction of greater agreement with observations, while in others it is in the opposite direction. The simulation shows a tendency to overestimate interannual variability of temperature and precipitation compared to observations, particularly during summer and over the Mediterranean regions. It is shown that in DJF, MAM and SON the RegCM interannual variability is primarily determined by the boundary forcing from HadAMH, while in JJA the internal model physics and resolution effects dominate over many subregions of the domain, and the RegCM has higher interannual variability than HadAMH. The precipitation trends simulated by the nested modeling system for the period 1961–1990 capture some features of the observed trends, in particular the cold season drying over the Mediterranean regions. Ensembles of simulations are, however, needed for a more robust assessment of the models capability to simulate climatic trends. Overall, this simulation is of good quality compared with previous nested RegCM experiments and will constitute the basis for the generation of climate change scenarios over the European region to be reported in future work.