Peculiarities of diurnal variations of the vertical gradient of the atmosphere refraction index in Eastern Russia

In this paper, diurnal variations of the vertical gradient of the atmosphere refraction index in the lower 300-m layer are computed and analysed in detail for a vast territory of Eastern Siberia and Far East of Russia by using 10-year observation data obtained at 32 aerological stations. In particular, it was found out that diurnal variation of the gradient is more diverse in summer and less diverse in fall. In the most north-easterly regions, unlike other climate zones where maximum gradient changes occur in summer and in winter, the greatest diurnal fluctuations of g _n are observed in spring. In the studied region, amplitudes of diurnal variations of g _n are significant and quite comparable with those of inter-seasonal oscillations of g _n .     

Effects of climate change and agronomic practice on changes in wheat phenology

Phenological changes in crops affect efficient agricultural production and can be used as important biological indicators of local and regional climate change. Although crop phenological changes and their responses to climate change, especially temperature, have been investigated, the impact of agronomic practice such as cultivar shifts and planted date changes on crop phenology remains unclear. Here, we used a long-term dataset (1981–2010) of wheat phenology and associated local weather data from 48 agro-meteorological stations in four temperature zones in China to analyze phenological changes of spring and winter wheat. Trend analysis method was used to estimate changes in the date of growth stages and the duration of growth phases, while sensitivity analysis method was used to qualify the response of growth phase duration to mean temperature (T_mean), total precipitation (PRE), and total sunshine duration (SSD). Using the Crop Environment Resource Synthesis-wheat model, we isolated the impacts of climate change, cultivar selection, and sowing date on phenological change of wheat. Results show that phenological changes were greatest in the warm-temperate zone. Sensitivity analysis indicates that growth phase duration was generally negatively related to T_mean and positively related to PRE and SSD. The positive sensitivity response to T_mean occurred in the tillering to jointing and sowing to maturity growth periods in the warmer temperature zones, suggesting that warmer temperatures during the overwintering period hampered effective vernalization in winter wheat. Modeling results further indicate that reductions in wheat growth duration caused by climate change could be offset by the introduction of new cultivars with high thermal requirements and accelerated with delayed sowing date.     

Effects of changing precipitation and warming on functional traits of zonal <Emphasis Type="Italic">Stipa</Emphasis> plants from Inner Mongolian grassland

The mechanisms driving changes in dominant plant species are the key for understanding how grassland ecosystems respond to climate change. In this study, we examined plant functional traits (morphological characteristics: plant height, leaf area, and leaf number; biomasses: aboveground, belowground, and total; and growth indices: root-to-shoot ratio, specific leaf area, and leaf mass ratio) of four zonal Stipa species (S. baicalensis, S. bungeana, S. grandis, and S. breviflora) from Inner Mongolian grassland in response to warming (control, +1.5, +2.0, +4.0, and +6.0?), changing precipitation (-30%, -15%, control, +15%, and +30%), and their combined effects via climate control chambers. The results showed that warming and changing precipitation had significant interactive effects, different from the accumulation of single-factor effects, on functional traits of Stipa species. The correlation and sensitivity of different plant functional traits to temperature and precipitation differed. Among the four species, the accumulation and variability of functional traits had greater partial correlation with precipitation than temperature, except for leaf number, leaf area, and specific leaf area, in S. breviflora, S. bungeana, and S. grandis. For S. baicalensis, the accumulation and variability of plant height, aboveground biomass, and root-to-shoot ratio only had significant partial correlation with precipitation. However, the variability of morphological characteristics, biomasses, and some growth indices, was more sensitive to temperature than precipitation in S. bungeana, S. grandis, and S. breviflora—except for aboveground biomass and plant height. These results reveal that precipitation is the key factor determining the growth and changes in plant functional traits in Stipa species, and that temperature mainly influences the quantitative fluctuations of the changes in functional traits.     

Projected Changes in Extreme High Temperature and Heat Stress in China

High temperature accompanied with high humidity may result in unbearable and oppressive weather. In this study, future changes of extreme high temperature and heat stress in mainland China are examined based on daily maximum temperature (T_x) and daily maximum wet-bulb globe temperature (T_w). T_w has integrated the effects of both temperature and humidity. Future climate projections are derived from the bias-corrected climate data of five general circulation models under the Representative Concentration Pathways (RCPs) 2.6 and 8.5 scenarios. Changes of hot days and heat waves in July and August in the future (particularly for 2020–50 and 2070–99), relative to the baseline period (1981–2010), are estimated and analyzed. The results show that the future T_x and T_w of entire China will increase by 1.5–5°C on average around 2085 under different RCPs. Future increases in T_x and T_w exhibit high spatial heterogeneity, ranging from 1.2 to 6°C across different regions and RCPs. By around 2085, the mean duration of heat waves will increase by 5 days per annum under RCP8.5. According to T_x, heat waves will mostly occur in Northwest and Southeast China, whereas based on T_w estimates, heat waves will mostly occur over Southeast China and the mean heat wave duration will be much longer than those from T_x. The total extreme hot days (T_x or T_w > 35°C) will increase by 10–30 days. Southeast China will experience the severest heat stress in the near future as extreme high temperature and heat waves will occur more often in this region, which is particularly true when heat waves are assessed based on T_w. In comparison to those purely temperature-based indices, the index T_w provides a new perspective for heat stress assessment in China.     

Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models

Worldwide, the majority of rapidly growing neighborhoods are found in the Global South. They often exhibit different building construction and development patterns than the Global North, and urban climate research in many such neighborhoods has to date been sparse. This study presents local-scale observations of net radiation (Q _* ) and sensible heat flux (Q _H ) from a lightweight low-rise neighborhood in the desert climate of Andacollo, Chile, and compares observations with results from a process-based urban energy-balance model (TUF3D) and a local-scale empirical model (LUMPS) for a 14-day period in autumn 2009. This is a unique neighborhood-climate combination in the urban energy-balance literature, and results show good agreement between observations and models for Q _* and Q _H . The unmeasured latent heat flux (Q _E ) is modeled with an updated version of TUF3D and two versions of LUMPS (a forward and inverse application). Both LUMPS implementations predict slightly higher Q _E than TUF3D, which may indicate a bias in LUMPS parameters towards mid-latitude, non-desert climates. Overall, the energy balance is dominated by sensible and storage heat fluxes with mean daytime Bowen ratios of 2.57 (observed Q _H /LUMPS Q _E )–3.46 (TUF3D). Storage heat flux (ΔQ _S ) is modeled with TUF3D, the empirical objective hysteresis model (OHM), and the inverse LUMPS implementation. Agreement between models is generally good; the OHM-predicted diurnal cycle deviates somewhat relative to the other two models, likely because OHM coefficients are not specified for the roof and wall construction materials found in this neighborhood. New facet-scale and local-scale OHM coefficients are developed based on modeled ΔQ _S and observed Q _* . Coefficients in the empirical models OHM and LUMPS are derived from observations in primarily non-desert climates in European/North American neighborhoods and must be updated as measurements in lightweight low-rise (and other) neighborhoods in various climates become available.     

Multivariate drought frequency estimation using copula method in Southwest China

This study reveals the impacts of climatic variable trends on drought severity in Xinjiang, China. Four drought indices, including the self-calibrating Palmer drought severity index (sc-PDSI), Erinç’s index (I _m), Sahin’s index (I _sh), and UNEP aridity index (AI), were used to compare drought severity. The ensemble empirical mode decomposition and the modified Mann-Kendall trend test were applied to analyze the nonlinear components and trends of the climatic variable and drought indices. Four and six climatic scenarios were generated in sc-PDSI, I _m, I _sh, and AI with different combinations of the observed and detrended climatic variables, respectively. In Xinjiang, generally increasing trends in minimal, average, and maximal air temperature (T _min, T _ave, T _max) and precipitation (P) were found, whereas a decreasing trend in wind speed at 2 m height (U ₂) was observed. There were significantly increasing trends in all of the four studied drought indices. Drought relief was more obvious in northern Xinjiang than in southern Xinjiang. The strong influences of increased P on drought relief and the weak influences of increased T _min, T _ave, and T _max on drought aggravation were shown by comparing four drought indices under different climate scenarios. Decreased U ₂ had a weak influence on drought, as shown by the AI in different climate scenarios. The weak influences of T and U ₂ were considered to be masked by the strong influences of P on droughts. Droughts were expected to be more severe if P did not increase, but were likely milder without an increase in air temperature and with a decrease in U ₂.     

Atmospheric circulation epochs and climate changes

The atmospheric circulation studies allow climate changes to be diagnosed and forecasted. Variations in occurrence frequencies of the atmospheric circulation forms W, E, and C (by the Vangengeim classification) and Z, M ₁, and M ₂ (by the Girs classification), which characterize climatic conditions in most of the Northern Hemisphere, are analyzed over a period of more than 100 years. It is shown that the occurrence frequency of the forms W, C, and M ₁ continually decreased, while that of the forms E and Z increased, which indicates a significant change in atmospheric circulation in the Northern Hemisphere during the last century. The occurrence frequency of the forms C and Z demonstrates specific features at inter-decade time scales. Correlations are found between accumulated sums of anomalies of occurrence frequencies of the atmospheric circulation forms C, (W + E), Z, and (M ₁ + M ₂) and inter-decade variations of the Earth’s rotation. The causes of these relationships are discussed along with possibilities of their use for diagnosis of climatic variations in the Northern Hemisphere.     

Investigation of dominant modes of monsoon ISO in the northwest and eastern Himalayan region

This study investigates the altitudinal variation of dominant modes of summer monsoon intra-seasonal oscillation (ISO) over the Northwest (NWH) and Eastern Himalayan (EH) region using (i) spatially scattered 133 number of station rainfall observations and (ii) latitudinal transect-wise (LT) rainfall variation, obtained from an observed interpolated gridded rainfall data for the period 1995–2004. The altitudinal variation of dominant modes of monsoon ISO were investigated by exploring the strong and weak phases of the principal components of 10–90 days bandpass rainfall data of June to September with respect to location specific station height. Investigation of frequency of days for light and moderate rainfall along with the occurrence of total seasonal rainy days has revealed existence of a rainfall maximum around 2100 m height for the NWH region. Similarly, the total seasonal rainy days of EH region was found to have maxima between 1100 and 1400 m height. Analyses of the spatially scattered station rainfall observation for the NWH region showed that the strong periods of ISO modes exist around 747.9 (±131.7) m and 2227.2 (±100.2) m heights. Over the EH region, the dominant modes of the monsoon ISO were found to be centred around 1200 m. Significant alterations of strong and weak phases of monsoon ISO as a response to altitudinal variation in the mountain surface were observed when latitudinal transect-wise variation of monsoon ISO modes were investigated.     

Relationship Between Fine-Particle Pollution and the Urban Heat Island in Beijing,China: Observational Evidence

Urbanization has led to a significant urban heat island (UHI) effect in Beijing in recent years. At the same time, air pollution caused by a large number of fine particles significantly influences the atmospheric environment, urban climate, and human health. The distribution of fine particulate matter (PM_2.5) concentration and its relationship with the UHI effect in the Beijing area are analyzed based on station-observed hourly data from 2012 to 2016. We conclude that, (1) in the last five years, the surface concentrations of PM_2.5 averaged for urban and rural sites in and around Beijing are 63.2 and 40.7 µg m^?3, respectively, with significant differences between urban and rural sites (ΔPM_2.5) at the seasonal, monthly and daily scales observed; (2) there is a large correlation between ΔPM_2.5 and the UHI intensity defined as the differences in the mean (ΔT_ave), minimum (ΔT_min), and maximum (ΔT_max) temperatures between urban and rural sites. The correlation between ΔPM_2.5 and ΔT_min (ΔT_max) is the highest (lowest); (3) a Granger causality analysis further shows that ΔPM_2.5 and ΔT_min are most correlated for a lag of 1–2 days, while the correlation between ΔPM_2.5 and ΔT_ave is lower; there is no causal relationship between ΔPM_2.5 and ΔT_max; (4) a case analysis shows that downwards shortwave radiation at the surface decreases with an increase in PM_2.5 concentration, leading to a weaker UHI intensity during the daytime. During the night, the outgoing longwave radiation from the surface decreases due to the presence of daytime pollutants, the net effect of which is a slower cooling rate during the night in cities than in the suburbs, leading to a larger ΔT_min.     

Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario

Assessing disease risk has become an important component in the development of climate change adaptation strategies. Here, the infection ability of leaf blast (Magnaporthe oryzae) was modeled based on the epidemiological parameters of minimum (T _min), optimum (T _opt), and maximum (T _max) temperatures for sporulation and lesion development. An infection ability response curve was used to assess the impact of rising temperature on the disease. The simulated spatial pattern of the infection ability index (IAI) corresponded with observed leaf blast occurrence in Indo-Gangetic plains (IGP). The IAI for leaf blast is projected to increase during the winter season (December–March) in 2020 (2010–2039) and 2050 (2040–2069) climate scenarios due to temperature rise, particularly in lower latitudes. However, during monsoon season (July–October), the IAI is projected to remain unchanged or even reduce across the IGP. The results show that the response curve may be successfully used to assess the impact of climate change on leaf blast in rice. The model could be further extended with a crop model to assess yield loss.     

Geo-spatial analysis of temporal trends of temperature and its extremes over India using daily gridded (1°×1°) temperature data of 1969–2005

Daily gridded (1°×1°) temperature data (1969–2005) were used to detect spatial patterns of temporal trends of maximum and minimum temperature (monthly and seasonal), growing degree days (GDDs) over the crop-growing season (kharif, rabi, and zaid) and annual frequencies of temperature extremes over India. The direction and magnitude of trends, at each grid level, were estimated using the Mann–Kendall statistics (α = 0.05) and further assessed at the homogeneous temperature regions using a field significance test (α=0.05). General warming trends were observed over India with considerable variations in direction and magnitude over space and time. The spatial extent and the magnitude of the increasing trends of minimum temperature (0.02–0.04 °C year^?1) were found to be higher than that of maximum temperature (0.01–0.02 °C year^?1) during winter and pre-monsoon seasons. Significant negative trends of minimum temperature were found over eastern India during the monsoon months. Such trends were also observed for the maximum temperature over northern and eastern parts, particularly in the winter month of January. The general warming patterns also changed the thermal environment of the crop-growing season causing significant increase in GDDs during kharif and rabi seasons across India. The warming climate has also caused significant increase in occurrences of hot extremes such as hot days and hot nights, and significant decrease in cold extremes such as cold days and cold nights.     

Preparation of frost atlas using different interpolation methods in a semiarid region of south of Iran

In this research, suitability of different kriging and inverse distance weighted (IDW) methods in estimating occurrence date of frost was evaluated. Data included minimum daily air temperature values from 27 meteorological stations of Fars province in southern Iran from 18 to 45 years. Data ranges of 0 to ?1.5, ?1.5 to ?3 and below ?3°C were considered as mild, moderate and severe frost intensities, respectively. Starting with the first day of autumn, iso-occurrence days for the frost intensities and occurrence probabilities (25%, 50%, 75% and 90%) were estimated using ordinary kriging, cokriging, residual kriging type 1 (RK1), residual kriging type 2 (RK2), universal kriging and IDW methods. In these models, the errors of estimated frost intensities at different probabilities were lowest in the RK2 model, but lack of establishment of spatial structure due to long distance between stations caused the predictions not to be acceptable in some cases. In a proposed method (modified inverse distance weighted, MIDW), the trend between the first and last days of frost occurrence with earth elevation was removed, and the reminder values were estimated by (IDW) method. Although, the errors for estimated frost dates by MIDW and RK2 methods were the same, but the MIDW method did not have the spatial establishment shortcoming. Furthermore, the simplicity and practicality of the MIDW method makes it a reasonable selection.     

Long-term variation of rainfall erosivity in Calabria (Southern Italy)

The changes in rainfall erosivity have been investigated using the rainfall erosivity factor (R) proposed for USLE by Wischmeier and Smith (R _W-S ) and some simplified indexes (the Fournier index modified by Arnoldus, F, a regional index spatial independent, R _Fr , and a regional index spatial dependent, R _Fs ) estimated by indirect approaches. The analysis has been carried out over 48 rainfall stations located in Calabria (Southern Italy) using data collected in the period 1936–2012 and divided in three sub-periods. The series of the erosivity indexes and of some precipitation variables have been analyzed for evidence of trends using standard methods. The simplified indexes suggested a general underestimation of the rainfall erosivity with respect to R _W-S . The mean underestimation ranged between 23 and 54 % for R _Fr and from 10 to 15 % for R _Fs . Both the sign and the magnitude of the trends were different for the different stations depending on the variable and sub-period considered. In general, the erosivity increased during the period 1936–1955 (1^st sub-period) and during the more recent sub-period (1992–2012, 3^rd sub-period), whereas it decreased during 1958–1977 (2^nd sub-period). The evidence of trends was generally higher for R _W-S than for R _Fr and R _Fs . Focusing on the most recent sub-period (3^rd sub-period), all the variables analyzed showed mainly increasing trends but with different magnitude. More particularly, R _W-S showed a mean increment of 29 %; F, R _Fr and R _Fs increased by 11, 15 and 18 %, respectively; the maximum intensity of 0.5-h precipitation increased by 5 %; and the annual precipitation increased by 22 %. Consequently, it remains difficult to define which precipitation variable plays the dominant role in the temporal variation of rainfall erosivity in the region. However, the overall results suggest that the indexes estimated by indirect procedures (F, R _Fr , and R _Fs ) should be used with caution for climate change analysis, despite they are used for practical purposes considering they are based on easily available information.     

A compact form for the analytic description of temperature dependence of saturation vapor pressure over plane surfaces of water and ice

A possibility is studied of extending the range of action of the simple three-parameter formula (ITS-90 scale) proposed in the previous work of the author [2] for the dependence of saturation vapor pressure E on temperature T within the range of 250 to 490 K. The results demonstrated that the dependence ln[E(T)/E(T _bas)] = (T - T _bas)[A - B(T - T _bas) + C(T - T _bas)²]/T with four sets of coefficients A, B, and C obtained using one base temperature Tbas equal to the temperature of triple point of water T _t = 273.16 K and two additional base values T _bas2 = 473.16 K and T _bas3 = 623.16 K makes it possible to approximate rather accurately the initial experimental and computed data in the temperature range from the point of homogeneous freezing of 235 K to the critical temperature of 647 K for liquid water and from 193 K to T _t for ice. A procedure used for obtaining the inverse function T(E) by solving the third-degree algebraic equation is validated. A hypothesis is proposed for the physical substantiation of additional base points in the form of “a noticeable appearance of dimers at the point T _bas2 and their 100% concentration at the temperature T _bas3.”     

Analysis of photosynthetically active radiation and applied parameterization model for estimating of PAR in the North China Plain

As photosynthetically active radiation (PAR) variability and PAR estimating methods play an important role in climate change and ecological process research, PAR variation trends and broadband global solar radiation (R _s ) ratios (PAR/R _s ) in the North China Plain (NCP) are examined using in situ PAR and R _s observed data for 2005 to 2011. The annual average PAR value found in the NCP is 22.9 mol m^?2 d^?1. The highest and lowest values were recorded at Changwu and Luancheng sites, respectively. The highest PAR/R _s value was found in Jiaozhouwan due to large water vapor volumes present in this area. PAR/R _s levels have increased in the NCP due to a decrease in fine aerosols and increase in water vapor concentration. From these analysis results, a parameterization model that can be applied to all sky conditions was checked. Empirical estimation model comparisons for obtaining PAR values indicate that model was least accurate when R _s was used independently. When the model included R _s, the clearness index (K _s) and the solar zenith angle, the model estimated PAR values with acceptable accuracy. A parameterization model was constructed by considering K _s and attenuation factors of PAR under clear weather conditions (ρ _clear). The improved parameterization model more accurately predicts values for local sites and for various observation sites.     

Effect of solubility limitation on hygroscopic growth and cloud drop activation of SOA particles produced from traffic exhausts

Hygroscopicity measurements of secondary organic aerosol (SOA) particles often show inconsistent results between the supersaturated and subsaturated regimes, with higher activity as cloud condensation nucleus (CCN) than indicated by hygroscopic growth. In this study, we have investigated the discrepancy between the two regimes in the Lund University (LU) smog chamber. Various anthropogenic SOA were produced from mixtures of different precursors: anthropogenic light aromatic precursors (toluene and m-xylene), exhaust from a diesel passenger vehicle spiked with the light aromatic precursors, and exhaust from two different gasoline-powered passenger vehicles. Three types of seed particles were used: soot aggregates from a diesel vehicle, soot aggregates from a flame soot generator and ammonium sulphate (AS) particles. The hygroscopicity of seed particles with condensed, photochemically produced, anthropogenic SOA was investigated with respect to critical supersaturation (s_c) and hygroscopic growth factor (gf) at 90% relative humidity. The hygroscopicity parameter κ was calculated for the two regimes: κ_sc and κ_gf, from measurements of s_c and gf, respectively. The two κ showed significant discrepancies, with a κ_gf /κ_sc ratio closest to one for the gasoline experiments with ammonium sulphate seed and lower for the soot seed experiments. Empirical observations of s_c and gf were compared to theoretical predictions, using modified Köhler theory where water solubility limitations were taken into account. The results indicate that the inconsistency between measurements in the subsaturated and supersaturated regimes may be explained by part of the organic material in the particles produced from anthropogenic precursors having a limited solubility in water.     

Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010

Oak pollen concentrations over the Houston-Galveston-Brazoria (HGB) area in southeastern Texas were modeled and evaluated against in-situ data. We modified the Community Multi-scale Air Quality (CMAQ) model to include oak pollen emission, dispersion, and deposition. The Oak Pollen Emission Model (OPEM) calculated gridded oak pollen emissions, which are based on a parameterized equation considering a plant-specific factor (C _e ), surface characteristics, and meteorology. The simulation period was chosen to be February 21 to April 30 in the spring of 2010, when the observed monthly mean oak pollen concentrations were the highest in six years (2009-2014). The results indicated C _e and meteorology played an important role in the calculation of oak pollen emissions. While C _e was critical in determining the magnitude of oak pollen emissions, meteorology determined their variability. In particular, the contribution of the meteorology to the variation in oak pollen emissions increased with the oak pollen emission rate. The evaluation results using in-situ surface data revealed that the model underestimated pollen concentrations and was unable to accurately reproduce the peak pollen episodes. The model error was likely due to uncertainty in climatology-based C _e used for the estimation of oak pollen emissions and inaccuracy in the wind fields from the Weather Research and Forecast (WRF) model.     

Comprehensive modeling of monthly mean soil temperature using multivariate adaptive regression splines and support vector machine

Soil temperature (T _s) and its thermal regime are the most important factors in plant growth, biological activities, and water movement in soil. Due to scarcity of the T _s data, estimation of soil temperature is an important issue in different fields of sciences. The main objective of the present study is to investigate the accuracy of multivariate adaptive regression splines (MARS) and support vector machine (SVM) methods for estimating the T _s. For this aim, the monthly mean data of the T _s (at depths of 5, 10, 50, and 100 cm) and meteorological parameters of 30 synoptic stations in Iran were utilized. To develop the MARS and SVM models, various combinations of minimum, maximum, and mean air temperatures (T _min, T _max, T); actual and maximum possible sunshine duration; sunshine duration ratio (n, N, n/N); actual, net, and extraterrestrial solar radiation data (R _s, R _n, R _a); precipitation (P); relative humidity (RH); wind speed at 2 m height (u ₂); and water vapor pressure (V_p) were used as input variables. Three error statistics including root-mean-square-error (RMSE), mean absolute error (MAE), and determination coefficient (R ²) were used to check the performance of MARS and SVM models. The results indicated that the MARS was superior to the SVM at different depths. In the test and validation phases, the most accurate estimations for the MARS were obtained at the depth of 10 cm for T _max, T _min, T inputs (RMSE = 0.71 °C, MAE = 0.54 °C, and R ² = 0.995) and for RH, V _p, P, and u ₂ inputs (RMSE = 0.80 °C, MAE = 0.61 °C, and R ² = 0.996), respectively.     

Crop modelling: towards locally relevant and climate-informed adaptation

A gap between the potential and practical realisation of adaptation exists: adaptation strategies need to be both climate-informed and locally relevant to be viable. Place-based approaches study local and contemporary dynamics of the agricultural system, whereas climate impact modelling simulates climate-crop interactions across temporal and spatial scales. Crop-climate modelling and place-based research on adaptation were strategically reviewed and analysed to identify areas of commonality, differences, and potential learning opportunities to enhance the relevance of both disciplines through interdisciplinary approaches. Crop-modelling studies have projected a 7–15% mean yield change with adaptation compared to a non-adaptation baseline (Nature Climate Change 4:1–5, 2014). Of the 17 types of adaptation strategy identified in this study as place-based adaptations occurring within Central America, only five were represented in crop-climate modelling literature, and these were as follows: fertiliser, irrigation, change in planting date, change in cultivar and area cultivated. The breath and agency of real-life adaptation compared to its representation in modelling studies is a source of error in climate impact simulations. Conversely, adaptation research that omits assessment of future climate variability and impact does not enable to provide sustainable adaptation strategies to local communities so risk maladaptation. Integrated and participatory methods can identify and reduce these sources of uncertainty, for example, stakeholder’s engagement can identify locally relevant adaptation pathways. We propose a research agenda that uses methodological approaches from both the modelling and place-based approaches to work towards climate-informed locally relevant adaptation.     

Spatial autocorrelation analysis of extreme precipitation in Iran

Spatial variations in extreme precipitation events make hydrological, climatological, social, environmental and agricultural effects on a country. This study presents the spatiotemporal autocorrelation analysis of extreme precipitation events over Iran using gridded data on daily precipitation for the period 1961–2010. The 95th percentile is considered as extreme precipitation factor. The spatial autocorrelation of extreme precipitation is examined by three commonly used spatial autocorrelation statistics, the G _i statistic index, Moran’s I global index, and Local Moran’s I (LISA) index, at the 95 and 99% significant confidence level. The results showed a strong significant spatial autocorrelation for extreme precipitation events with the highest Moran’s I value in January. The positive significant autocorrelation of extreme precipitation is observed over the southern parts of the Caspian Sea and Zagros Mountains ranges, while the negative significant autocorrelation is observed over the central and eastern parts of country. In spring and summer the positive autocorrelation cores displace from the Zagros Mountains ranges to the northwestern and southeastern parts.