Climate Trend Analysis Research Articles

Wave- and Anemometer-Based Sea Surface Wind (WASWind) for Climate Change Analysis*

Abstract Ship-based measurements of sea surface wind speed display a spurious upward trend due to increases in anemometer height. To correct this bias, the authors constructed a new sea surface wind dataset from ship observations of wind speed and wind wave height archived in the International Comprehensive Ocean–Atmosphere Data Set (ICOADS). The Wave- and Anemometer-based Sea surface Wind (WASWind) dataset is available for wind velocity and scalar speed at monthly resolution on a 4° × 4° longitude–latitude grid from 1950 to 2008. It substantially reduces the upward trend in wind speed through height correction for anemometer-measured winds, rejection of spurious Beaufort winds, and use of estimated winds from wind wave height. The reduced global upward trend is smallest among the existing global datasets of in situ observations and comparable with those of reanalysis products. Despite the significant reduction of globally averaged wind speed trend, WASWind features rich spatial structures in trend pattern, making it a valuable dataset for studies of climate changes on regional scales. Not only does the combination of ship winds and wind wave height successfully reproduce major modes of seasonal-to-decadal variability; its trend patterns are also physically consistent with sea level pressure (SLP) measurements. WASWind is in close agreement with wind changes in satellite measurements by the Special Sensor Microwave Imagers (SSM/Is) for the recent two decades. The agreement in trend pattern with such independent observations illustrates the utility of WASWind for climate trend analysis. An application to the South Asian summer monsoon is presented.

Using the quantile regression method to analyze changes in climate characteristics

Possibilities to use the non-parametric regression analysis method, named the quantile regression, for the estimation of changes in climate characteristics are considered. When analyzing the trends of climatic series, the quantile regression method enables to get the information on trends along the whole range of quantile values from 0 to 1 of dependent variable distributions, that is more informative than the use of traditional regression technique, based on the least-squares method (LSM) and enabling to obtain trend estimations for average values of the dependent variable only. Trend estimation errors for various methods are analyzed. The computation of quantile regression parameters for real climatic series is executed. Series of meteorological variables of the diurnal resolution, which characterize the surface climate (minimal, average, and maximal diurnal temperatures) and free atmosphere climate (temperature of isobaric surfaces up to 30 hPa inclusive) are considered. Seasonal peculiarities in trend manifestation at different parts of quantile range of these meteorological values are discussed. Concerning the problem of the analysis of climate trends, the quantile regression method seems to be perspective from the point of view of more detailed understanding of processes in the climate system, such as the surface and tropospheric warming, stratospheric cooling, long-period changes in characteristics of climate variability and extremity.

Analysis of climatic trends in data from the agrometeorological station of Bologna-Cadriano, Italy (1952–2007)

Agriculture is highly exposed to climate change, as farming activities directly depend on climatic conditions. Knowledge of the extent of such change and of related phenomena will help to answer the questions posed by society about adaptation strategies. The global situation is well described by the Fourth IPCC assessment report (IPCC 2007), but local studies are important to understand the impact and the priorities to adopt in adaptation strategies. In this study a historical set of meteorological data, collected during the period 1952–2007 at the University of Bologna (Italy) agrometeorological station, was analysed. Several indexes, such as Frost Severity Index, number of hot days, number of rainy days, etc., were calculated, and their trends in time were analysed. The results show a scenario of increasing temperatures and evapotranspiration, a decrease in rainy days and a deepening of the watertable. The effect of these changes on agriculture will be a decrease in water availability, an increase in heat stress in plants and an increase in drought risk.

Basin-Scale Water Resources Assessment in Oklahoma under Synthetic Climate Change Scenarios Using a Fully Distributed Hydrologic Model

Climate change resulting from the enhanced greenhouse effect is expected to have significant implications for the hydrological cycle. Several studies have pointed out the importance of basin-scale investigations for determining regional impacts on water resources, including the effects of floods and droughts. In this study, a fully distributed hydrologic model is used to assess the potential impacts of climate change on water availability in a basin in Oklahoma (United States). With this aim, the hydrologic model was applied for current conditions as well as under the hypotheses of climate variations represented by scenarios consistent with a climatic trend analysis generated using a stochastic weather model. Hydrologic simulations indicate that streamflow and evapotranspiration reflect variations in precipitation differently. Positive trends in precipitation result in an increase in surface and groundwater resources, while evapotranspiration is only affected slightly due to the higher soil moisture in the basin. Sensitivity analyses of the evapotranspiration and runoff changes to precipitation variations confirm these results. Comparisons of the impacts of the precipitation trend on surface and groundwater resources showed that the increase of surface water resources is ∼3 times greater, implying the groundwater system is affected less by climate change. The use of a distributed model also provided insight on the spatial variation of the water balance components. Results showed that the most significant increases of soil moisture (∼60%) are located along the river network and in the flat areas of the basin, characterized by a higher frequency of saturation excess runoff. In summary, climate change scenarios in this region produced an increase in water resources that can have beneficial impacts, but these positive effects are tempered by the increasing potential for flood risk. The increase of this risk has been evaluated as well in this analysis.

Quantitative evaluation of climatic variability and risks for wheat yield in India

This study comprises (1) an analysis of recent climate trends at two sites in north-west India (Ludhiana in Punjab and Delhi) and (2) an impact and risk assessment for wheat yields associated with climatic variability. North-west Indian agriculture is dominated by rice-wheat rotation in which the wheat season (‘rabi’, November to March) is characterized by predominantly dry conditions—superimposed by very high inter-annual variability of rainfall (17 to 260 mm in Ludhiana and <1 to 155 mm in Delhi). While rainfall remained without discernable trend over the last three decades, minimum and average temperatures showed increasing trends of 0.06 and 0.03°C year − 1, respectively, at Ludhiana. The site in (metropolitan) Delhi was apparently influenced by city-effects, which was noticeable from the decrease in solar radiation of 0.09 MJ m − 2 day − 1 year − 1. The CERES-wheat model was used to calculate yields of rainfed wheat that were at both locations highly correlated with seasonal rainfall. An assessment framework was developed to quantify yield impacts due to rainfall variability in three steps: (1) data from different years were aggregated into four classes, i.e., years with scarce, low, moderate, and high rainfall, (2) yield records of each rainfall class were ranked according to yield to facilitate (3) a comparison of yields with identical rank, i.e. among the best yield of each class, the second-best, etc. The class with moderate rainfall was taken as baseline yield to compute yield impacts of other rainfall scenarios. Years with scarce rainfall resulted in only 34% (Ludhiana) and 35% (Delhi) of the baseline yield. The yields in years with low rainfall accounted for 61% (Delhi) and 49% (Ludhiana) of the baseline yields. In Ludhiana, high rainfall years resulted in 200% yield as compared to the baseline yield, whereas they reached only 105% in Delhi. Low-intensity (1× and 3×) irrigation decreased the relative yield losses, but entailed a higher vulnerability in terms of absolute yield losses. Only high-intensity (4×) irrigation buffered wheat yields against adverse rainfall years. Early sowing was beneficial for wheat yields under all rainfall scenarios. The framework could be a valuable decision-support tool at the farm level where seasonal rainfall variability is high.

Climatic trends in temperature, zonal flow, and stationary planetary waves from NCEP/NCAR reanalysis data

A detailed analysis of climatic trends in the longitudinally averaged temperature, zonal wind velocity, and activity of a stationary planetary wave with the zonal wave number 1 (SPW1) is made for January. The results of analysis indicate that marked climatic temperature variations having opposite signs in the low and high latitudes are observed. These variations cause the relevant variations in the intensity and arrangement of maxima of tropospheric jet flows and, thereby, are responsible for changes in SPW1 propagation conditions. SPW1 propagation from the troposphere into the upper atmosphere is calculated with a linearized model by using the distributions of zonal mean flow that are characteristic of the 1960s and the early 21st century. These calculations indicate that, over the past 40 years, the propagation conditions have improved “on average” and the calculated SPW1 amplitude in the stratosphere and mesosphere of the winter hemisphere has increased substantially. Analysis of the amplitudes of the zonal wind velocity for SPW1 that were obtained from the NCEP/NCAR data is consistent with the results of simulation and shows that some enhancement of SPW1 activity in the lower stratosphere has been actually observed in recent years. These variations in the amplitudes are also accompanied by the enhancement of SPW1 interannual variability.

Simultaneous analysis of climatic trends in multiple variables: an example of application of multivariate statistical methods

This paper introduces into the research on trends in climate elements the multivariate statistical methods, namely principal component analysis (PCA) and cluster analysis, and demonstrates the benefits of their use. We also introduce the idea of normalization of the trends by their confidence interval, which facilitates the comparison of trends among different variables and allows their fair treatment by the multivariate methods. The study is performed for 11 climate elements at 21 stations in the Czech Republic. Temperatures are rising in winter, spring and summer, but decreasing in autumn. Consistent with these changes are trends in sunshine duration, cloudiness and daily temperature range. Correlation analysis and PCA confirm the mutual relationships among the trends in these variables in all seasons. The two methods also uncover other groups of variables whose trends vary similarly at individual stations, which, however, occur in several seasons only, not throughout the year. This implies that the trend analyses based on seasonal values should be preferred to analyses of annual trends. The cluster analysis of stations allows the quantification of the spatial consistency of trends. The groupings of stations are spatially incoherent and seasonally variable, which indicates that local peculiarities of the relatively complex terrain affect the station trends to a considerable extent. Copyright © 2005 Royal Meteorological Society.

Analysis of wheat yield and climatic trends in Mexico

Wheat yields in Mexico, which represent an important measure of breeding and management progress in developing world wheat production, have increased by 25% over the past two decades. Using a combination of mechanistic and statistical models, we show that much of this increase can be attributed to climatic trends in Northwest states, in particular cooling of growing season nighttime temperatures. This finding suggests that short-term prospects for yield progress are smaller than suggested by recent yield increases, and that future gains will require an intensification of research and extension efforts aimed at raising wheat yields.

Spatial patterns and recent trends in the climate of tropical rainforest regions.

We present an analysis of the mean climate and climatic trends of tropical rainforest regions over the period 1960-1998, with the aid of explicit maps of forest cover and climatological databases. Until the mid-1970s most regions showed little trend in temperature, and the western Amazon experienced a net cooling probably associated with an interdecadal oscillation. Since the mid-1970s, all tropical rainforest regions have experienced a strong warming at a mean rate of 0.26 +/- 0.05 degrees C per decade, in synchrony with a global rise in temperature that has been attributed to the anthropogenic greenhouse effect. Over the study period, precipitation appears to have declined in tropical rainforest regions at a rate of 1.0 +/- 0.8% per decade (p < 5%), declining sharply in northern tropical Africa (at 3-4% per decade), declining marginally in tropical Asia and showing no significant trend in Amazonia. There is no evidence so far of a decline in precipitation in eastern Amazonia, a region thought vulnerable to climate-change-induced drying. The strong drying trend in Africa suggests that this should be a priority study region for understanding the impact of drought on tropical rainforests. We develop and use a dry-season index to study variations in the length and intensity of the dry season. Only African and Indian tropical rainforests appear to have seen a significant increase in dry-season intensity. In terms of interannual variability, the El Niño-Southern Oscillation (ENSO) is the primary driver of temperature variations across the tropics and of precipitation fluctuations for large areas of the Americas and southeast Asia. The relation between ENSO and tropical African precipitation appears less direct.

Statistical analysis of regional climate trends in Saxony, Germany

This study focuses on changes in irradiance, temperature, precipitation, evaporation, snow cover, and water balance in Saxony (eastern Germany) over the past 50 yr. It had 2 main objec- tives: (1) collection of all available climatological data with daily resolution, (2) statistical analysis of the climate. Time series of more than 600 meteorological stations from Saxony and the surrounding regions have been organized in the Saxon climate databank. This databank contains tools for homo- geneity tests and trend analysis of climatologic time series. This makes it possible to calculate derived and complex quantities from single climate elements. About half of the time series tested were suffi- ciently homogeneous for a regional climate analysis of Saxony. The most important results of the trend analysis are: (1) marked decrease in summer rainfall (-10 to -30%); (2) significant increase in winter precipitation; (3) increase in heavy rainfall events during early summer; (4) increase in the length and frequency of dry periods in both vegetation periods; (5) increase in temperature in all sea- sons, and especially in winter (>2°C in northern Saxony); (6) increase in irradiance and potential evaporation by about 7% in the last 30 years.

Analysis of climate trends in North Carolina (1949–1998)

North Carolina has one of the most complex climates in the United States (U.S.). Analysis of the climate in this state is critical for agricultural and planning purposes. Climate patterns and trends in North Carolina are analyzed for the period 1949–1998. Precipitation, minimum temperature, and maximum temperature are analyzed on seasonal and annual time scales using data collected from the National Weather Service Cooperative Observer Network. Additionally, changes in patterns of occurrence of the last spring freeze and first fall freeze are investigated. Linear time series slopes are analyzed to investigate the spatial and temporal trends of climate variability in North Carolina. Spatial analysis of climate variability across North Carolina is performed using a geographic information system. While most trends are local in nature, there are general statewide patterns. Precipitation in North Carolina has increased over the past 50 years during the fall and winter seasons, but decreased during the summer. Temperatures during the last 10 years are warmer than average, but are not warmer than those experienced during the 1950s. The warm season has become longer, as measured by the dates of the last spring freeze and first fall freeze. Generally, the last 10 years were the wettest of the study period. These conclusions are consistent with earlier studies that show that the difference between the maximum and minimum temperatures is decreasing, possibly due to increased cloud cover and precipitation. Similarly, these results show that temperature patterns are in phase with the North Atlantic Oscillation and precipitation patterns appear to be correlated with the Pacific Decadal Oscillation.

Long-term phyto-, ornitho- and ichthyophenological time-series analyses in Estonia

This study analyzes a long-term phenological time series for the impact assessment of climate changes on Estonian nature and for the methodological study of the possible limitations of using phenological time series for climate trend analyses. These limiting factors can influence the results of studies more than the real impact of climate changes, which may have a much smaller numeric value. The 132-year series of the arrival of the skylark (Alauda arvensis) and the white wagtail (Motacilla alba), the 78-year series of the blossoming of the wood anemone (Anemone nemorosa), the bird cherry (Padus racemosa), apple trees (Malus domestica) and lilacs (Syringa vulgaris), and the 44-year series of the spawning of pike (Esox lucius) and bream (Abramis brama) were studied at three selected observation points in Estonia. The study of the phenological time series shows that Estonian springs have, on the basis of the database, advanced 8 days on average over the last 80-year period; the last 40-year period has warmed even faster.

Window technique for climate trend analysis

Climatic characteristics are affected by various systematic and occasional impacts: besides the changes in the observing system (locations of the stations of the meteorological network, instruments, observing procedures), the possible local-scale and global natural and antropogenic impacts on climatic conditions should be taken into account. Apart from the predictability problems, the phenomenological analysis of the climatic variability and the determination of past persistent climatic anomalies are significant problems, among other aspects, as evidence of the possible anomalous behavior of climate or for climate impact studies. In this paper, a special technique for the identification of such “shifts” in the observational series is presented. The existence of these significant shorter or longer term changes in the mean characteristics for the properly selected adjoining periods of time is the necessary condition for the formation of any more or less unidirectional climatic trends. Actually, the window technique is based on a complete set of orthogonal functions. The sensitivity of the proposed model on its main parameters is also investigated. This method is applied for hemispheric and Hungarian data series of the mean annual surface temperature.

Weed Seed Bank and Vegetation at the Beginning and End of the First Cycle of a 4-Course Crop Rotation with Minimal Weed Control

Maize water suitability (MWS) model was developed at growth stage scale. Frequency and severity of drought were evaluated by combining MWS estimates and agricultural meteorological drought indexes. The MWS at each growth stage was calculated by using maize observational data and conventional meteorological data at 52 sites in Liaoning during the period from 1981 to 2010. Based on the climatic trend and abrupt change analysis, spatiotemporal dynamics of MWS were investigated. Meanwhile, occurrence of agricultural drought and its severity were also estimated. The results showed that the variation of MWS largely differed at different growth stages. Climatic abrupt change happened in 1994, 1996 and 1999 at the stages of emergence to seven leaves (II), jointing to tasseling (IV) and physiological maturity to maturity (VI). During the past 30 years, MWS showed an obvious increasing trend at the stages of sowing to emergence(I) , seven leaves to jointing(III), IV and tasseling to physiological maturity(V), while it showed a decreasing trend at the stages of II and VI, and that at VI stage was statistically significant. In addition, the climatic trend of MWS showed apparently spatial variability. The frequencies of drought at different severities varied with maize growth stages. Areas of high variability of MWS were located in the Northwest and South of Liaoning at the stages of I , II , III and VI, where were also the regions of high frequency of mid- and severe-drought. At the stages of IV and V, the frequency of drought was low and only light- and mid-drought occurred in few areas. In conclusion, the regional mean MWS could be capable to reasonably assess the agricultural drought in Liaoning at the regional scale.

Adaptation to Climate Change in Water Management, Agrobiodiversity and Forestry with Special Reference to Nepal

Analysis of recent climatic trends reveals a significant sign of warming in recent decades which has been more pronounced at higher altitudes. Climate change scenarios for Nepal show considerable convergence on continued warming, Warming trends have already had significant impacts in the Nepal Himalayas -most significantly in terms of glacier retreat such as increase in size and volume of glacial lakes, making them more prone to glacial lake outburst flooding (GLOF). This contributes to enhanced variability of river flows. The indepth analysis of water resources in Nepal identifies two critical impacts of climate change- GLOFs and variability of river runoff- both of which pose significant impacts not only on hydropower, but also on rural livelihoods and agriculture. The range of practices that can be used to adapt the climate change is diverse, and includes changes in behavior, structural policy based responses, technological or managerial responses. Key Words: Adaptation, Climate change, Forestry, Agrobiodiversity, GLOF DOI: 10.3126/init.v2i1.2532 The Initiation Vol.2(1) 2008 pp113-120