Investigation of temporal and spatial climate variability and aridity of Iran

The aim of this research is to study the spatial and temporal variability of aridity in Iran, through analysis of temperature and precipitation trends during the 48-year period of 1961–2008. In this study, four different aridity criteria have been used to investigate the aridity situation. These aridity indexes included Lang’s index or rain factor, Budyko index or radiational index of dryness, UNEP aridity index, and Thornthwaite moisture index. The results of the analysis indicated that the highest and lowest mean temperatures occurred in July and January respectively in all locations. Among the study locations, Ahvaz with 37.1 °C and Kermanshah with 20.2 °C has the highest and lowest in July. For January, the highest was 12.4 °C for Ahvaz and the lowest was ?4.5 °C for Hamedan and Kermanshah together. The range of monthly mean temperature of study locations indicated that the maximum and minimum difference between day and night temperatures, almost in all study locations, occurred in September and January, respectively, and the highest and lowest fluctuation of temperature was observed in Kerman and Tehran. The temperature anomalies showed that the most significant increasing temperature occurred at the beginning of twenty-first century (2000–2008) in all locations. The long-term mean of monthly rainfall showed that, in most study locations, the maximum and minimum of mean precipitation occurred in winter and summer, respectively. Rasht with 1,355 mm had the highest and Yazd with 55 mm had the lowest of total precipitation compared with other locations. According to precipitation anomalies, all locations experienced dry and wet periods, but generally dry periods occurred more often especially in the beginning of twenty-first century. According to applied different aridity indexes, all the study locations often experienced semi-arid to arid climate, severe water deficit to desert climate, arid to hyperarid climate, and semi-arid climate during the study period.     

The temporal variability of soil wetness and its impact on climate

The temporal variability of soil wetness and its interactions with the atmosphere were studied using a general circulation model of the atmosphere. It was found that time series of soil wetness computed by the model contain substantial amounts of variance at low frequencies. Long time-scale anomalies of soil moisture resemble the red noise response of the soil layer to white noise rainfall forcing. The dependence of the temporal variability of soil moisture on potential evaporation and precipitation is discussed.     

Short-term temporal variability of atmospheric surface pressure and wind speed in the Canadian Arctic

In this study, the spatial differences and interannual fluctuations in temporal variability of surface pressure and wind speed on different timescales at 12 locations in the Canadian Arctic are documented. Temporal variability is defined as the mean-squared value of time tendencies smoothed by running means over different intervals. It is shown that variability on timescales of up to 1 month is itself highly variable, both in space and time. Due to the significant impacts from the immediate geographical environment, for surface wind speed, these variations show no spatial pattern on a continental scale, and only a few persistent trends over periods of more than 10 years. Also, spatial and temporal anomalies do not significantly depend on timescale. Contrary to this, spatial and temporal variations in the variability of surface pressure and its changes with time show well-defined regional similarities, as well as a strong spatial and temporal dependence on timescale. As a result, variability of surface pressure on timescales between 1 and 3 days increases from the northeast region of the domain towards the southwest. On longer timescales, this spatial gradient is reversed. The consistent spatial pattern across the study domain suggests that variability of surface pressure is primarily governed by large-scale atmospheric processes, and is to a large extent independent of the exact geographical setting.     

A global ocean temperature and altimeter data assimilation system for studies of climate variability

 An ocean data assimilation (ODA) system which can assimilate both temperature and altimeter observations has been applied to the global ocean and tested between January 1993–October 1996. A statistical method has been used to convert sea surface height (SSH) anomalies observations from TOPEX/POSEIDON into synthetic temperature profiles. The innovative aspect of this method is the introduction of time dependency in the correlations used to transform the altimeter observations into temperature corrections. The assimilation system is based on a univariate variational optimal interpolation scheme applied to assimilate both in situ and synthetic temperature profiles. In addition, a longer global analysis for the upper-ocean temperature starting from January 1979 and ending November 1997, has been produced to examine the skill of sea temperature assimilation with a rather simple and practical method. The temperature analysis shows encouraging improvement over a corresponding ocean simulation when compared to independent (not assimilated) temperature data both at seasonal and interannual time scales. However, the univariate data assimilation of hydrographic data does not result in an improvement of the velocity field. In fact the assimilation of sparse in situ data can introduce unrealistic spatial variability in the temperature field which affects the velocity field in a negative way. This deficiency is partially overcome when we also assimilate altimeter observations since the coverage is complete and uniform for this data. In particular, our study shows that temperature corrections due to the altimeter signal have a positive impact on the current system in the tropical Pacific. Received: 28 May 2000 / Accepted: 6 November 2000     

Three Eurasian teleconnection patterns: spatial structures,temporal variability,and associated winter climate anomalies

The Eurasian (EU) pattern is a distinct teleconnection pattern observed in boreal winter. Since the EU pattern was first identified, three types have been reported in the literature: the conventional EU pattern; the type 1 EU pattern, or Scandinavian (SCAND) pattern; and the type 2 EU pattern, or East Atlantic/West Russia (EATL/WRUS) pattern. Based on several reanalysis and observational datasets, the three EU patterns are extracted using the rotated empirical orthogonal function method. In order to provide a further distinction and understanding of the three EU patterns, a comprehensive side-by-side comparison is performed among them including their temporal variability, horizontal and vertical structure, related stationary Rossby wave activity, impact on climate, and possible driving factors associated with external forcing. The results reveal that all three EU patterns are characterised by a clear quasi-barotropic wave-train structure, but each has a distinct source and centre of action. Accordingly, their impacts on the precipitation and surface air temperature also differ from one other. Further evidence suggests that the conventional EU pattern is likely driven by anomalous sea surface temperatures (SST) over the North Atlantic, in which process the transient eddies are actively involved. The SCAND pattern is partly maintained by the vorticity source over Western Europe, which arises from the anomalous convergence/divergence over the Mediterranean and is efficiently driven by the tropical and southern Indian Ocean SST via divergent circulation. The EATL/WRUS pattern shows some linkage to the North American snow cover, and the involved process remains unclear and needs further investigation.     

Assessment of climate variability and trend on wheat productivity in West Bengal,India: crop growth simulation approach

Wheat is the second important cereal crop after rice in West Bengal. During last three decades, due to climate fluctuations and variability, the productivity of this crop remains almost constant, bringing the threat of food security of this State. The objectives of the present study were to assess the trend of climatic variables (rainfall, rainy days, and temperature) over six locations covering five major agro-climatic sub-zones of West Bengal and to estimate the variability of potential, simulated yield using crop simulation model (DSAATv4.5) and the yield gap with actual yield. There were no significant change of rainfall and rainy days in annual, seasonal and monthly scale at all the study sites. In general, the maximum temperature is decreasing throughout West Bengal. Except for Birbhum, the minimum temperature increased significantly in different study sites. District average yield of wheat varied from 1757 kg ha^?1 at Jalpaiguri to 2421 kg ha^?1at Birbhum. The actual yield trend ranged from ??4.7 kg ha^?1 year^?1 at Nadia to 32.8 kg ha^?1 year^?1 at Birbhum. Decreasing trend of potential yield was observed in Terai (Jalpaiguri), New Alluvial Zone (Nadia) and Coastal saline zone (South 24 Parganas), which is alarming for food security in West Bengal.     

Coping with climate variability and climate change in La Ceiba,Honduras

La Ceiba, Honduras, a city of about 200,000 people, lies along the Caribbean Sea, nestled against a mountain range and the Rio Cangrejal. The city faces three flooding risks: routine flooding of city streets due to the lack of a stormwater drainage system; occasional major flooding of the Rio Cangrejal, which flows through the city; and flooding from heavy rainfall events and storm surges associated with tropical cyclones. In this study, we applied a method developed for the U.S. Agency for International Development and then worked with stakeholders in La Ceiba to understand climate change risks and evaluate adaptation alternatives. We estimated the impacts of climate change on the current flooding risks and on efforts to mitigate the flooding problems. The climate change scenarios, which addressed sea level rise and flooding, were based on the Intergovernmental Panel on Climate Change estimates of sea level rise (Houghton et al. 2001) and published literature linking changes in temperature to more intense precipitation (Trenberth et al., Bull Am Meteorol Soc, 84:1205–1217, 2003) and hurricanes (Knutson and Tuleya, J Clim, 17:3477–3495, 2004). Using information from Trenberth et al., Bull Am Meteorol Soc, 84:1205–1217, (2003) and Knutson and Tuleya, J Clim, 17:3477–3495, 2004, we scaled intense precipitation and hurricane wind speed based on projected temperature increases. We estimated the volume of precipitation in intense events to increase by 2 to 4% in 2025 and by 6 to 14% by 2050. A 13% increase in intense precipitation, the high scenario for 2050, could increase peak 5-year flood flows by about 60%. Building an enhanced urban drainage system that could cope with the estimated increased flooding would cost one-third more than building a system to handle current climate conditions, but would avoid costlier reconstruction in the future. The flow of the Rio Cangrejal would increase by one-third from more intense hurricanes. The costs of raising levees to protect the population from increased risks from climate change would be about $1 million. The coast west of downtown La Ceiba is the most vulnerable to sea level rise and storm surges. It is relatively undeveloped, but is projected to have rapid development. Setbacks on coastal construction in that area may limit risks. The downtown coastline is also at risk and may need to be protected with groins and sand pumping. Stakeholders in La Ceiba concluded that addressing problems of urban drainage should be a top priority. They emphasized improved management of the Rio Cangrejal watershed and improved storm warnings to cope with risks from extreme precipitation and cyclones. Adoption of risk management principles and effective land use management could also help reduce risks from current climate and climate change.     

The seasonal footprinting mechanism in large ensemble simulations of the second generation Canadian earth system model: uncertainty due to internal climate variability

Climate Dynamics - Previous studies indicated that the wintertime North Pacific Oscillation (NPO) could exert marked impacts on the following winter El Niño-Southern Oscillation (ENSO) via the...     

Characterizing spatial and temporal variability of crop yield caused by climate and irrigation in the North China Plain

Grain yields of wheat and maize were obtained from national statistics and simulated with an agricultural system model to investigate the effects of historical climate variability and irrigation on crop yield in the North China Plain (NCP). Both observed and simulated yields showed large temporal and spatial variability due to variations in climate and irrigation supply. Wheat yield under full irrigation (FI) was 8?t?ha^?1 or higher in 80% of seasons in the north, it ranged from 7 to 10?t?ha^?1 in 90% of seasons in central NCP, and less than 9?t?ha^?1 in 85% of seasons in the south. Reduced irrigation resulted in increased crop yield variability. Wheat yield under supplemental irrigation, i.e., to meet only 50% of irrigation water requirement [supplemental irrigation (SI)] ranged from 2.7 to 8.8?t?ha^?1 with the maximum frequency of seasons having the range of 4?C6?t?ha^?1 in the north, 4?C7?t?ha^?1 in central NCP, and 5?C8?t?ha^?1 in the south. Wheat yield under no irrigation (NI) was lower than 1?t?ha^?1 in about 50% of seasons. Considering the NCP as a whole, simulated maize yield under FI ranged from 3.9 to 11.8?t?ha^?1 with similar frequency distribution in the range of 6?C11.8?t?ha^?1 with the interval of 2?t?ha^?1. It ranged from 0 to 11.8?t?ha^?1, uniformly distributed into the range of 4?C10?t?ha^?1 under SI, and NI. The results give an insight into the levels of regional crop production affected by climate and water management strategies.     

Learning with practitioners: climate change adaptation priorities in a Canadian community

Adaptation is already a necessary response to climate change for northern communities. The City of Prince George, in British Columbia, Canada, has been adjusting to impacts for years and there is a high level of local awareness of climate change. The purpose of this study was to collaborate with City staff and other organizations to undertake action-oriented research with the goal of creating a local adaptation strategy. Steps taken toward this goal included: producing downscaled climate scenarios; facilitating a workshop with local practitioners to prioritize impacts; gathering public feedback regarding impacts; and triangulating sources of information to determine community adaptation priorities. Changes to forests and increased flooding are the top local adaptation priorities, and impacts related to transportation, severe weather and water supply are high priorities. Other impacts, such as health effects and agricultural changes, are also important but did not rank highly using a risk framework focused on negative physical effects. Local impacts, actions the City is undertaking to address them and suggestions for implementing adaptation measures are summarized. The process of creating an adaptation strategy has proven highly valuable in Prince George and has precipitated further engagement and action. Due to the low profile of adaptation and limited resources in many communities, researchers and practitioners must capitalize on opportunities to incorporate adaptation into existing plans and processes. Lessons from the Prince George experience can be applied to other communities as they strive to effectively adapt to climate change.     

Spatial and temporal variability of summer rainfall over Ethiopia from observations and a regional climate model experiment

The spatial and temporal variability of rainfall over Ethiopia during the summer (JJAS) season is studied using observations (both station and satellite based) and model simulation data. The simulation dataset is generated using the fourth version of the International Center for Theoretical Physics Regional Climate Model (RegCM4) for the period 1989–2005. Ethiopia is first divided into 12 homogeneous regions using criteria including rotated empirical orthogonal function (REOF), spatial correlation, seasonal cycles, and topographical features. Spatially averaged observed and simulated rainfall time series are then generated and analyzed for each region. Standardized rainfall anomalies of the observations and the simulated data are highly correlated over the northern, western, northeastern, central, and southwestern regions, while a weak correlation is found over the border regions of the country. The dominant modes of rainfall variability are identified using REOF, while time–frequency variations of different dominant modes are described by wavelet analysis. The first leading patterns of rainfall and upper wind (averaged between 100 and 300 hPa) are highly correlated and exhibit similar features between simulation and observations over the northern, western, southwestern, and eastern regions of Ethiopia. The second loading pattern of rainfall and the first loading pattern of low-level wind (averaged between 850 and 1,000 hPa) exhibit a dipole structure across the southwestern and northeastern regions of the country. The dominant signals in the first rotated principal component (RPC) of rainfall and upper level wind fields show a period of 4–5 and 2–3 years, while the dominant signals in the second RPC show a period of 2–3 years at a 0.05 significance level. The correlations of significant RPCs across gauge, gridded, and model rainfall fields with that of low and upper level winds show the presence of a significant relationship (correlation exceeding ～0.6). Overall, the RegCM4 shows a good performance in simulating the spatial and temporal variability of precipitation over Ethiopia.     

Two measures of progress in adapting to climate change

Adaptation will play a key role in determining the economic and social costs of climate change. One important measure of adaptation is reductions in deaths caused by climate events. This paper uses two new data sets to test the hypothesis that, in recent years, climate events cause less deaths than in the past. Using data on deaths caused by natural disasters and data on skin cancer death rates in warmer and cooler US states, this paper reports evidence in favor of the adaptation progress hypothesis.     

Northern hemisphere winter atmospheric climate: modes of natural variability and climate change

Under anthropogenic climate change it is possible that the increased radiative forcing and associated changes in mean climate may affect the “dynamical equilibrium” of the climate system; leading to a change in the relative dominance of different modes of natural variability, the characteristics of their patterns or their behavior in the time domain. Here we use multi-century integrations of version three of the Hadley Centre atmosphere model coupled to a mixed layer ocean to examine potential changes in atmosphere-surface ocean modes of variability. After first evaluating the simulated modes of Northern Hemisphere winter surface temperature and geopotential height against observations, we examine their behavior under an idealized equilibrium doubling of atmospheric CO₂. We find no significant changes in the order of dominance, the spatial patterns or the associated time series of the modes. Having established that the dynamic equilibrium is preserved in the model on doubling of CO₂, we go on to examine the temperature pattern of mean climate change in terms of the modes of variability; the motivation being that the pattern of change might be explicable in terms of changes in the amount of time the system resides in a particular mode. In addition, if the two are closely related, we might be able to assess the relative credibility of different spatial patterns of climate change from different models (or model versions) by assessing their representation of variability. Significant shifts do appear to occur in the mean position of residence when examining a truncated set of the leading order modes. However, on examining the complete spectrum of modes, it is found that the mean climate change pattern is close to orthogonal to all of the modes and the large shifts are a manifestation of this orthogonality. The results suggest that care should be exercised in using a truncated set of variability EOFs to evaluate climate change signals.     

Understanding social resilience to climate variability in primary enterprises and industries

Resource-dependent industries are particularly vulnerable to climate change, and their ability to adapt will be as critical to society as to the natural systems upon which they rely. More than ever, resource-users will need to anticipate, and prepare for, climate-related changes, and institutions will need to be particularly supportive, if resource industries and the extended social systems dependent on them are to be sustained. I examine the capacity of cattle-graziers in Australia to cope and adapt to climate variability as a precursor for understanding their vulnerability to climate change by assessing: (i) their perception of risk, (ii) their capacity to plan, learn and reorganise, (iii) their proximity to the thresholds of coping, and (iv) their level of interest in adapting to change. Graziers perceived themselves to be resilient to climate variability in their perceptions of climate risk, reorganising capacity, coping, and interest in adapting. Their dependency on the grazing resource and use of seasonal climate forecasts were significant influences, suggesting that resilience could be enhanced. Facilitated collaborative learning amongst graziers and other stakeholders may assist to develop strategic skills, increasing climate awareness, developing financial security and adopt climate tools such as seasonal climate forecasts. Enhanced strategies for coping with climate variability will provide a way for encouraging gradual, incremental adjustments for climate adaptation.     

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.     

A method for incorporating climate variability in climate change impact assessments: Sensitivity of river flows in the Eden catchment to precipitation scenarios

Interest in the impacts of climate change is ever increasing. This is particularly true of the water sector where understanding potential changes in the occurrence of both floods and droughts is important for strategic planning. Climate variability has been shown to have a significant impact on UK climate and accounting for this in future climate change projections is essential to fully anticipate potential future impacts. In this paper a new resampling methodology is developed which includes the variability of both baseline and future precipitation. The resampling methodology is applied to 13 CMIP3 climate models for the 2080s, resulting in an ensemble of monthly precipitation change factors. The change factors are applied to the Eden catchment in eastern Scotland with analysis undertaken for the sensitivity of future river flows to the changes in precipitation. Climate variability is shown to influence the magnitude and direction of change of both precipitation and in turn river flow, which are not apparent without the use of the resampling methodology. The transformation of precipitation changes to river flow changes display a degree of non-linearity due to the catchment’s role in buffering the response. The resampling methodology developed in this paper provides a new technique for creating climate change scenarios which incorporate the important issue of climate variability.     

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.     

North Atlantic warming: patterns of long-term trend and multidecadal variability

Climate fluctuations in the North Atlantic Ocean have wide-spread implications for Europe, Africa, and the Americas. This study assesses the relative contribution of the long-term trend and variability of North Atlantic warming using EOF analysis of deep-ocean and near-surface observations. Our analysis demonstrates that the recent warming over the North Atlantic is linked to both long-term (including anthropogenic and natural) climate change and multidecadal variability (MDV, ~50–80 years). Our results suggest a general warming trend of 0.031 ± 0.006°C/decade in the upper 2,000 m North Atlantic over the last 80 years of the twentieth century, although during this time there are periods in which short-term trends were strongly amplified by MDV. For example, MDV accounts for ~60% of North Atlantic warming since 1970. The single-sign basin-scale pattern of MDV with prolonged periods of warming (cooling) in the upper ocean layer and opposite tendency in the lower layer is evident from observations. This pattern is associated with a slowdown (enhancement) of the North Atlantic thermohaline overturning circulation during negative (positive) MDV phases. In contrast, the long-term trend exhibits warming in tropical and mid-latitude North Atlantic and a pattern of cooling in regions associated with major northward heat transports, consistent with a slowdown of the North Atlantic circulation as evident from observations and confirmed by selected modeling results. This localized cooling has been masked in recent decades by warming during the positive phase of MDV. Finally, since the North Atlantic Ocean plays a crucial role in establishing and regulating the global thermohaline circulation, the multidecadal fluctuations discussed here should be considered when assessing long-term climate change and variability, both in the North Atlantic and at global scales.     

A climate trend analysis of Ethiopia: examining subseasonal climate impacts on crops and pasture conditions

Ethiopia experiences significant climate-induced drought and stress on crop and livestock productivity, contributing to widespread food insecurity. Here, we present subseasonal crop water stress analyses that indicate degrading, growing conditions along Ethiopia’s eastern highlands, including productive and populated highland regions. These seasonally shifting areas of increasing water stress stretch from the north to south across eastern Ethiopia, intersecting regions of acute food insecurity and/or high population. Crop model simulations indicate that between 1982 and 2014, parts of eastern Amhara and eastern Oromia experienced increasing water deficits during the critical sowing, flowering, and ripening periods of crop growth. These trends occurred while population in these regions increased by 143% between 2000 and 2015. These areas of enhanced crop water stress in south-central Ethiopia coincide with regions of high population growth and ongoing crop extensification. Conversely, large regions of relatively unpopulated western Ethiopia are becoming wetter. These areas may therefore be good targets for agricultural development.     

Interannual variability of Mediterranean evaporation and its relation to regional climate

Gridded monthly evaporation data for 1958–2006 from the Woods Hole Oceanographic Institution data set are used to investigate interannual variability of Mediterranean evaporation during cold and hot seasons and its relation to regional atmospheric dynamics, sea surface temperature and atmospheric elements of the hydrological cycle. The first EOF mode of Mediterranean evaporation, explaining more than 50% of its total variance, is characterized by the monopole pattern both in winter and summer. However, despite structural similarity, the EOF-1 of Mediterranean evaporation is affected by different climate signals in cold and hot seasons. During winter the EOF-1 is associated with the East Atlantic teleconnection pattern. In summer, there is indication of tropical influence on the EOF-1 of Mediterranean evaporation (presumably from Asian monsoon). Both in winter and summer, principal components of EOF-1 demonstrate clear interdecadal signals (with a stronger signature in summer) associated with large sea surface temperature anomalies. The results of a sensitivity analysis suggest that in winter both the meridional wind and the vertical gradient of saturation specific humidity (GSSH) near the sea surface contribute to the interdecadal evaporation signal. In summer, however, it is likely that the signal is more related to GSSH. Our analysis did not reveal significant links between the Mediterranean evaporation and the North Atlantic Oscillation in any season. The EOF-2 of evaporation accounts for 20% (11%) of its total variance in winter (in summer). Both in winter and summer the EOF-2 is characterized by a zonal dipole with opposite variations of evaporation in western and eastern parts of the Mediterranean Sea. This mode is associated presumably with smaller scale (i.e., local) effects of atmospheric dynamics. Seasonality of the leading modes of the Mediterranean evaporation is also clearly seen in the character of their links to atmospheric elements of the regional hydrological cycle. In particular, significant links to precipitation in some regions have been found in winter, but not in summer.