Multi-year fluctuations of temperature and precipitation: The gray area of climate change

The issue of whether the secular climate (twentieth century) is stationary or changing to some new semi-permanent state is clouded by the presence of so-called climate fluctuations. The twentieth century climate record of the United States reveals a substantial number of decadal fluctuations which occur in all seasons for both temperature and precipitation. Recent examples of such behavior include changes in winter and summer temperature variability and increases in transition season precipitation. Statistical evidence suggests that a substantial portion of these fluctuations, even those which are remarkably unusual, are merely manifestations of a stochastic process which possesses weak year-to-year persistence as viewed from an a posteriori perspective. The implications of this result are particularly important with respect to the formulation of physical causes of the fluctuations. The results emphasize the desirability of well-founded clearly-stated a priori theories of climate change as well as the limited usefulness of widely used climate normals.     

Localized climate change scenarios of mean temperature and precipitation over Switzerland

There is a growing need of the climate change impact modeling and adaptation community to have more localized climate change scenario information available over complex topography such as in Switzerland. A gridded dataset of expected future climate change signals for seasonal averages of daily mean temperature and precipitation in Switzerland is presented. The basic scenarios are taken from the CH2011 initiative. In CH2011, a Bayesian framework was applied to obtain probabilistic scenarios for three regions within Switzerland. Here, the results for two additional Alpine sub-regions are presented. The regional estimates have then been downscaled onto a regular latitude-longitude grid with a resolution of 0.02° or roughly 2 km. The downscaling procedure is based on the spatial structure of the climate change signals as simulated by the underlying regional climate models and relies on a Kriging with external drift using height as auxiliary predictor. The considered emission scenarios are A1B, A2 and the mitigation scenario RCP3PD. The new dataset shows an expected warming of about 1 to 6 °C until the end of the 21st century, strongly depending on the scenario and the lead time. Owing to a large vertical gradient, the warming is about 1 °C stronger in the Alps than in the Swiss lowlands. In case of precipitation, the projection uncertainty is large and in most seasons precipitation can increase or decrease. In summer a distinct decrease of precipitation can be found, again strongly depending on the emission scenario.     

Farmer perceptions of climate change: Associations with observed temperature and precipitation trends,irrigation, and climate beliefs

How individuals perceive climate change is linked to whether individuals support climate policies and whether they alter their own climate-related behaviors, yet climate perceptions may be influenced by many factors beyond local shifts in weather. Infrastructure designed to control or regulate natural resources may serve as an important lens through which people experience climate, and thus may influence perceptions. Likewise, perceptions may be influenced by personal beliefs about climate change and whether it is human-induced. Here we examine farmer perceptions of historical climate change, how perceptions are related to observed trends in regional climate, how perceptions are related to the presence of irrigation infrastructure, and how perceptions are related to beliefs and concerns about climate change. We focus on the regions of Marlborough and Hawke’s Bay in New Zealand, where irrigation is utilized on the majority of cropland. Data are obtained through analysis of historical climate records from local weather stations, interviews (n = 20), and a farmer survey (n = 490). Across both regions, no significant historical trends in annual precipitation and summer temperatures since 1980 are observed, but winter warming trends are significant at around 0.2–0.3 °C per decade. A large fraction of farmers perceived increases in annual rainfall despite instrumental records indicating no significant trends, a finding that may be related to greater perceived water availability associated with irrigation growth. A greater fraction of farmers perceived rainfall increases in Marlborough, where irrigation growth has been most substantial. We find those classes of farmers more likely to have irrigation were also significantly more likely to perceive an increase in annual rainfall. Furthermore, we demonstrate that perceptions of changing climate – regardless of their accuracy – are correlated with increased belief in climate change and an increased concern for future climate impacts. Those farmers that believe climate change is occurring and is human induced are more likely to perceive temperature increases than farmers who believe climate change is not occurring and is not human induced. These results suggest that perceptions are influenced by a variety of personal and environmental factors, including infrastructure, which may in turn alter decisions about climate adaptation.     

Optimal detection and attribution of climate change: sensitivity of results to climate model differences

Fingerprint techniques for the detection of anthropogenic climate change aim to distinguish the climate response to anthropogenic forcing from responses to other external influences and from internal climate variability. All these responses and the characteristics of internal variability are typically estimated from climate model data. We evaluate the sensitivity of detection and attribution results to the use of response and variability estimates from two different coupled ocean atmosphere general circulation models (HadCM2, developed at the Hadley Centre, and ECHAM3/LSG from the MPI für Meteorologie and Deutsches Klimarechenzentrum). The models differ in their response to greenhouse gas and direct sulfate aerosol forcing and also in the structure of their internal variability. This leads to differences in the estimated amplitude and the significance level of anthropogenic signals in observed 50-year summer (June, July, August) surface temperature trends. While the detection of anthropogenic influence on climate is robust to intermodel differences, our ability to discriminate between the greenhouse gas and the sulfate aerosol signals is not. An analysis of the recent warming, and the warming that occurred in the first half of the twentieth century, suggests that simulations forced with combined changes in natural (solar and volcanic) and anthropogenic (greenhouse gas and sulfate aerosol) forcings agree best with the observations.     

径流对气候变化的敏感性分析

全球变暖愈来愈引起社会各界的关注 ,本文利用月水文模型 ,采取假定气候方案 ,以黄河流域为例 ,分析了径流对气候变化的敏感性。结果表明 ,径流对降水变化的响应较气温变化显著 ;一般情况下 ,半干旱地区径流较半湿润地区对气候变化敏感 ,人类活动的影响可在一定程度上削弱径流对气候变化的敏感性     

Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa

We describe the nature of recent (50 year) rainfall variability in the summer rainfall zone, South Africa, and how variability is recognised and responded to on the ground by farmers. Using daily rainfall data and self-organising mapping (SOM) we identify 12 internally homogeneous rainfall regions displaying differing parameters of precipitation change. Three regions, characterised by changing onset and timing of rains, rainfall frequencies and intensities, in Limpopo, North West and KwaZulu Natal provinces, were selected to investigate farmer perceptions of, and responses to, rainfall parameter changes. Village and household level analyses demonstrate that the trends and variabilities in precipitation parameters differentiated by the SOM analysis were clearly recognised by people living in the areas in which they occurred. A range of specific coping and adaptation strategies are employed by farmers to respond to climate shifts, some generic across regions and some facilitated by specific local factors. The study has begun to understand the complexity of coping and adaptation, and the factors that influence the decisions that are taken.     

Linking climate change and health outcomes: Examining the relationship between temperature,precipitation and birth weight in Africa

This paper examined the relationship between birth weight, precipitation, and temperature in 19 African countries. We matched recorded birth weights from Demographic and Health Surveys covering 1986 through 2010 with gridded monthly precipitation and temperature data derived from satellite and ground-based weather stations. Observed weather patterns during various stages of pregnancy were also used to examine the effect of temperature and precipitation on birth weight outcomes. In our empirical model we allowed the effect of weather factors to vary by the dominant food production strategy (livelihood zone) in a given region as well as by household wealth, mother's education and birth season. This allowed us to determine if certain populations are more or less vulnerable to unexpected weather changes after adjusting for known covariates. Finally we measured effect size by observing differences in birth weight outcomes in women who have one low birth weight experience and at least one healthy birth weight baby. The results indicated that climate does indeed impact birth weight and at a level comparable, in some cases, to the impact of increasing women's education or household electricity status.     

Climate sensitivity and climate change under strong forcing

A version of the National Centre for Atmospheric Research (NCAR) coupled climate model is integrated under current climate conditions and in a series of experiments with climate forcings ranging from modest to very strong. The purpose of the experiments is to investigate the nature and behaviour of the climate feedback/sensitivity of the model, its evolution with time and climate state, the robustness of model parameterizations as forcing levels increase, and the possibility of a “runaway” warming under strong forcing. The model is integrated for 50 years, or to failure, after increasing the solar constant by 2.5, 10, 15, 25, 35, and 45% of its control value. The model successfully completes 50 years of integration for the 2.5, 10, 15, and 25% solar constant increases but fails for increases of 35% and 45%. The effective global climate sensitivity evolves with time and analysis indicates that a new equilibrium will be obtained for the 2.5, 10, and 15% cases but that runaway warming is underway for the 25% increase in solar constant. Feedback processes are analysed both locally and globally in terms of longwave and shortwave, clear-sky/surface, and cloud forcing components. Feedbacks in the system must be negative overall and of sufficient strength to balance the positive forcing if the system is to attain a new equilibrium. Longwave negative feedback processes strengthen in a reasonably linear fashion as temperature increases but shortwave feedback processes do not. In particular, solar cloud feedback becomes less negative and, for the 25% forcing case, eventually becomes positive, resulting in temperatures that “run away”. The conditions under which a runaway climate warming might occur have previously been investigated using simpler models. For sufficiently strong forcing, the greenhouse effect of increasing water vapour in a warmer atmosphere is expected to overwhelm the negative feedback of the longwave cooling to space as temperature increases. This is not, however, the reason for the climate instability experienced in the GCM. Instead, the model experiences a “cloud feedback” warming whereby the decrease in cloudiness that occurs when temperature increases beyond a critical value results in an increased absorption of solar radiation by the system, leading to the runaway warming.     

Quantifying the sensitivity of simulated climate change to model configuration

This study used “factor separation” to quantify the sensitivity of simulated present and future surface temperatures and precipitation to alternative regional climate model physics components. The method enables a quantitative isolation of the effects of using each physical component as well as the combined effect of two or more components. Simulation results are presented from eight versions of the Mesoscale Modeling System Version 5 (MM5), one-way nested within one version of the Goddard Institute for Space Studies Atmosphere-Ocean Global Climate Model (GISS AOGCM). The MM5 simulations were made at 108 km grid spacing over the continental United States for five summers in the 1990s and 2050s. Results show that the choice of cumulus convection parameterization is the most important “factor” in the simulation of contemporary surface summer temperatures and precipitation over both the western and eastern USA. The choice of boundary layer scheme and radiation package also increases the range of model simulation results. Moreover, the alternative configurations give quite different results for surface temperature and precipitation in the 2050s. For example, simulated 2050s surface temperatures by the scheme with the coolest 1990s surface temperatures are comparable to 1990s temperatures produced by other schemes. The study analyzes the spatial distribution of 1990s to 2050s projected changes in the surface temperature for the eight MM5 versions. The predicted surface temperature change at a given grid point, averaged over all eight model configurations, is generally about twice the standard deviation of the eight predicted changes, indicating relative consensus among the different model projections. Factor separation analysis indicates that the choice of cumulus parameterization is the most important modeling factor amongst the three tested contributing to the computed 1990s to 2050s surface temperature change, although enhanced warming over many areas is also attributable to synergistic effects of changing all three model components. Simulated ensemble mean precipitation changes, however, are very small and generally smaller than the inter-model standard deviations. The MM5 versions therefore offer little consensus regarding 1990s to 2050s changes in precipitation rates.     

Interdecadal variability of regional climate change: implications for the development of regional climate change scenarios

Summary Illustrative examples are discussed of the interdecadal variability features of the regional climate change signal in 5 AOGCM transient simulations. It is shown that the regional precipitation change signal is characterized by large variability at decadal to multidecadal scales, with the structure of the variability varying markedly across regions. Conversely, the regional temperature change signal shows low interdecadal variability. Results are compared across scenarios, models and different realizations with the same model. Our analysis indicates that, at the decadal scale, linear scaling of the regional climate change signal by the global temperature change works relatively well for temperature but less so for precipitation. The nonlinear fraction of the climate change signal tends to decrease with the magnitude of the signal. The implications of interdecadal variability for the generation of regional climate change scenarios are discussed, in particular concerning the use of multi-experiment ensembles to produce such scenarios.     

Recent trends in regional air temperature and precipitation and links to global climate change in the Maharlo watershed,Southwestern Iran

Trends in air temperature and precipitation data are investigated for linkages to global warming and climate change. After checking for serial correlation with trend-free pre-whitening procedure, the Mann–Kendall test is used to detect monotonic trends and the Mann–Whitney test is used for trend step change. The case study is Maharlo watershed, Southwestern Iran, representing a semi-arid environment. Data are for the 1951–2011 period, from four temperature sites and seven precipitation sites. A homogeneity test investigates regional similarity of the time series data. The results include mean annual, mean annual maximum and minimum and seasonal analysis of air temperature and precipitation data. Mean annual temperature results indicate an increasing trend, while a non-significant trend in precipitation is observed in all the stations. Furthermore, significant phase change was detected in mean annual air temperature trend of Shiraz station in 1977, indicating decreasing trend during 1951–1976 and increasing trend during 1977–2011. The annual precipitation analysis for Shiraz shows a non-significant decrease during 1951–1976 and 1977–2011. The result of homogeneity test reveals that the studied stations form one homogeneous region. While air temperature trends appear as regional linkage to global warming/global climate change, more definite outcome requires analysis of longer time series data on precipitation and air temperature.     

Local temperature estimation under climate change

Summary A methodology to estimate the space-time distribution of daily mean temperature under climate change is developed and applied to a central Nebraska case study. The approach is based on the analysis of the Markov properties of atmospheric circulation pattern (CP) types, and a stochastic linkage between daily (here 500hPa) CP types and daily mean temperatures. Historical data and general circulation model (GCM) output of daily CP corresponding to 1 × CO₂ and 2 × CO₂ scenarios are considered. The relationship between spatially averaged geopotential height of the 500 hPa surface — within each CP type — and daily mean temperature is described by a nonparametric regression technique. Time series of daily mean temperatures corresponding to each of these cases are simulated and their statistical properties are compared. Under the climate of central Nebraska, the space-time response of daily mean temperature to global climate change is variable. In general, a warmer climate appears to cause about 5°C increase in the winter months, a smaller increase in other months with no change in July and August. The sensitivity of the results to the GCM utilized should be considered.On leave from the Department of Meteorology, Eötvós Loránd University, Budapest, Hungary.With 14 Figures     

The sensitivity of the tropical circulation and Maritime Continent precipitation to climate model resolution

The dependence of the annual mean tropical precipitation on horizontal resolution is investigated in the atmospheric version of the Hadley Centre General Environment Model. Reducing the grid spacing from about 350 km to about 110 km improves the precipitation distribution in most of the tropics. In particular, characteristic dry biases over South and Southeast Asia including the Maritime Continent as well as wet biases over the western tropical oceans are reduced. The annual-mean precipitation bias is reduced by about one third over the Maritime Continent and the neighbouring ocean basins associated with it via the Walker circulation. Sensitivity experiments show that much of the improvement with resolution in the Maritime Continent region is due to the specification of better resolved surface boundary conditions (land fraction, soil and vegetation parameters) at the higher resolution. It is shown that in particular the formulation of the coastal tiling scheme may cause resolution sensitivity of the mean simulated climate. The improvement in the tropical mean precipitation in this region is not primarily associated with the better representation of orography at the higher resolution, nor with changes in the eddy transport of moisture. Sizeable sensitivity to changes in the surface fields may be one of the reasons for the large variation of the mean tropical precipitation distribution seen across climate models.     

A bulk mass flux convection scheme for climate model: description and moisture sensitivity

A convection scheme for climate model is developed based on Tiedtke’s (Mon Weather Rev 117:1779–1800, 1989) bulk mass flux framework and is evaluated with observational data and cloud resolving model simulation data. The main differences between the present parameterization and Tiedtke’s parameterization are the convection trigger, fractional entrainment and detrainment rate formulations, and closure method. Convection is triggered if the vertical velocity of a rising parcel is positive at the level at which the parcel is saturated. The fractional entrainment rate depends on the vertical velocity and buoyancy of the parcel as well as the environmental relative humidity. For the fractional detrainment rate, a linear decrease in the updraft mass flux above maximum buoyancy level is assumed. In the closure method, the cloud base mass flux is determined by considering both cloud layer instability and subcloud layer turbulent kinetic energy as controlling factors in the strength of the convection. The convection scheme is examined in a single column framework as well as using a general circulation model. The present bulk mass flux (BMF) scheme is compared with a simplified Relaxed Arakawa-Schubert (RAS) scheme. In contrast to the RAS, which specifies the cloud top, cloud top height in BMF depends on environmental properties, by considering the conditions of both the parcel and its environment in a fractional entrainment and detrainment rate formulations. As a result, BMF shows improved sensitivity in depth and strength of convection on environmental humidity compared to RAS, by strengthening coupling between cloud and environment. When the mid to lower troposphere is dry, the cloud resolving model and BMF produce cloud top around the dry layer and moisten the layer. In the framework of general circulation model, enhanced coupling between convection and environmental humidity in BMF results in improved representation of eastward propagating intraseasonal variability in the tropics—the Madden-Julian oscillation.