Evaluating the vegetation growing season changes in the arid region of northwestern China

Temperature has long been accepted as the major controlling factor in determining vegetation phenology in the middle and higher latitudes. The influence of water availability is often overlooked even in arid and semi-arid environments. We compared vegetation phenology metrics derived from both in situ temperature and satellite-based normalized difference vegetation index (NDVI) observations from 1982 to 2006 by an example of the arid region of northwestern China. From the satellite-based results, it was found the start of the growing season (SOS) advanced by 0.37 days year^?1 and the end of the growing season (EOS) delayed by 0.61 days year^?1 in Southern Xinjiang over 25 years. In the Tianshan Mountains, the SOS advanced by 0.35 days year^?1 and the EOS delayed by 0.31 days year^?1. There were almost no changes in Northern Xinjiang. Compared with satellite-based results, those estimates based on temperature contain less details of spatial variability of vegetation phenology. Interestingly, they show different and at times reversed spatial patterns from the satellite results arising from water limitation. Phenology metrics derived from temperature and NDVI conclude that water limitation of onset of the growing season is more severe than the cessation. Phenology spatial patterns of four oases in Southern Xingjiang show that, on average, there is a delay of the SOS of 1.6 days/10 km of distance from the mountain outlet stations. Our results underline the importance of water availability in determining the vegetation phenology in arid regions and can lead to important consequences in interpreting the possible change of vegetation phenology with climate.     

Evaluation of the Community Land Model 3.5 with carbon and nitrogen cycles (CLM3.5CN) at a Tibetan grassland site

The Tibetan plateau plays an important role in energy and carbon cycles by providing an elevated heat source and by storing a large amount of soil carbon due to low temperature. The main vegetation of the plateau is alpine grassland. This study evaluates performance of Community Land Model 3.5 with carbon and nitrogen cycles (CLM3.5CN) over a alpine grassland in the Tibetan plateau in terms of energy and carbon fluxes in conditions of reasonable phenology and initial carbon pool comparable to observations. Comparison between model and observation shows following features. The model captures the magnitude of maximum leaf area index (LAI) but underestimats leaf mass. Net ecosystem exchange (NEE) is significantly underestimated during the growing season and soil temperature is also underestimated throughout a year with higher negative bias in winter than in other seasons. In order to examine the cause of the model deficiencies, we design four sensitivity tests: seasonal mulch; shallow rooting depth; reduction of critical soil moisture to limit the decomposition rate; smaller specific leaf area (SLA). Considering seasonal mulch improves the negative bias of soil temperature during dormant season has little effect on the NEE during the growing seasson. Underestimation of NEE during the growing season is partly due to underestimated decomposition rate which results from underestimated soil temperature and deep root placement in the soil column. Underestimation of latent heat flux during summer is partly due to use of large SLA in the model. Other deficiencies are also discussed.     

天山新疆段植被物候特征及其气候响应

基于MODIS的MCD12Q2数据,采用趋势分析和相关性分析方法,结合遥感降水和气温数据产品,探求了天山新疆段2001—2014年植被物候的时空变化及其影响因素的相对作用。天山新疆段植被物候始期呈明显的垂直地带性分布特征,集中于3月10日至5月15日,全区14年平均值为3月20日;植被物候末期具有纬度地带性分布特征,集中于10月1日至10月25日。天山新疆段植被物候始期在山区呈不显著推迟趋势,绿洲和平原呈不显著提前趋势;植被物候末期主要呈不显著提前趋势;降水量和气温是影响天山植被物候期的重要因素。物候始期受当年春季气温的影响最为显著,也受到前一年冬季降水量的影响,其与降水量呈正相关,与气温呈负相关。夏季和秋季降水量是天山新疆段植被物候末期的主要影响因素。     

Agrometeorological study of crop drought vulnerability and avoidance in northeast of Iran

Drought is one of the crucial environmental factors affecting crop production. Synchronizing crop phenology with expected or predicted seasonal soil moisture supply is an effective approach to avoid drought impact. To assess the potential for drought avoidance, this study investigated the long-term climate data of four locations (Bojnourd, Mashhad, Sabzevar, and Torbat Heydarieh) in Khorasan province, in the northeast of Iran, with respect to the four dominant crops (common bean, lentil, peanut, and potato). Weekly water deficit defined as the difference between weekly precipitation and weekly potential evapotranspiration was calculated. Whenever the weekly water deficit was larger than the critical water demand of a crop, the probability for drought was determined. Results showed that Sabzevar has the highest average maximum temperature (24.6 °C), minimum temperature (11.7 °C), weekly evapotranspiration (32.1 mm), and weekly water deficit (28.3 mm) and has the lowest average weekly precipitation (3.8 mm). However, the lowest mean maximum temperature (19.7 °C), minimum temperature (6.9 °C), weekly evapotranspiration (22.5 mm), and weekly water deficit (17.5 mm) occur in Bojnourd. This location shows the shortest period of water deficit during the growing season for all crops except potato, which also experienced drought at the end of the growing season. Sabzevar and Torbat Heydarieh experienced the highest probability of occurrence and longest duration of drought during the growing season for all crops. The result of this study will be helpful for farmers in order to reduce drought impact and enable them to match crop phenology with periods during the growing season when water supply is more abundant.     

Specification of thermal growing season in temperate China from 1960 to 2009

A number of studies have reported an extension of the thermal growing season in response to the warming climate during recent decades. However, the magnitude of extension depends heavily on the threshold temperature used: for a given area, a small change in the threshold temperature results in significant differences in the calculated thermal growing season. Here, we specified the threshold temperature for determining the thermal growing season of local vegetation across 326 meteorological stations in temperate China by using vegetation phenology based on satellite imagery. We examined changes in the start, end, and length of the thermal growing season from 1960 to 2009. The threshold temperatures for determining the start and end increased strongly with increasing mean annual temperature. Averaged across temperate China, the start of the thermal growing season advanced by 8.4?days and the end was delayed by 5.7?days, resulting in a 14.1-day extension from 1960 to 2009. The thermal growing season was intensively prolonged (by 0.59?day/year) since the mid-1980s owing to accelerated warming during this period. This extension was similar to that determined by a spatially fixed threshold temperature of 5?°C, but the spatial patterns differed, owing to differences in the threshold temperature and to intra-annual heterogeneity in climate warming. This study highlights the importance of specifying the temperature threshold for local vegetation when assessing the influences of climate change on thermal growing season, and provides a method for determining the threshold temperature from satellite-derived vegetation phenology.     

Effects of rainfall amount and frequency on vegetation growth in a Tibetan alpine meadow

Over the past decades, rainfall amount and frequency changed considerably on the Tibetan Plateau. However, how altered rainfall pattern affects vegetation growth and phenology in Tibetan alpine grasslands is poorly understood. In this study, we investigated the long-term effects of rainfall amount and frequency on production (i.e., aboveground biomass, AGB) and phenology of three perennial plants in a Tibetan alpine meadow from 1994 to 2005. Growth period (i.e., the dates from greening to senescence) was referred to plant phenology here. Our results showed that annual precipitation and total rainfall from large events (≥ 5 mm per day) were mainly distributed in the growing season, which increased significantly from 1994 to 2005 with more increment in May and July (p?<?0.05). Total AGB and growth periods of three plants were linearly correlated with annual precipitation and total rainfall from large events, but have insignificant correlations with total rainfall from small events (< 5 mm per day) and rainfall frequency (including small, large, and all events). The results suggest that aboveground plant production and phenology are more sensitive to changes in large rainfall events (≥ 5 mm per day) than small events (< 5 mm per day) in the alpine meadow ecosystems.     

Accelerated climate change and its potential impact on Yak herding livelihoods in the eastern Tibetan plateau

The Tibetan Plateau has experienced rapid warming like most other alpine regions. Regional assessments show rates of warming comparable with the arctic region and decreasing Asian summer monsoons. We used meteorological station daily precipitation and daily maximum and minimum temperature data from 80 stations in the eastern Tibetan Plateau of southwest China to calculate local variation in the rates and seasonality of change over the last half century (1960–2008). Daily low temperatures during the growing season have increased greatly over the last 24 years (1984–2008). In sites of markedly increased warming (e.g., Deqin, Yunnan and Mangya, Qinghai), daily and growing season daily high temperatures have increased at a rate above 5 °C/100 years. In Deqin, precipitation prior to the 1980s fell as snow whereas in recent decades it has shifted to rain during March and April. These shifts to early spring rains are likely to affect plant communities. Animals like yaks adapted to cold climates are also expected to show impacts with these rising temperatures. This region deserves further investigation to determine how these shifts in climate are affecting local biodiversity and livelihoods.     

Spatiotemporal change in China’s climatic growing season: 1955–2000

The timing, length, and thermal intensity of the climatic growing season in China show statistically significant changes over the period of 1955 to 2000. Nationally, the average start of the growing season has shifted 4.6–5.5 days earlier while the average end has moved 1.8–3.7 days later, increasing the length of the growing season by 6.9–8.7 days depending on the base temperature chosen. The thermal intensity of the growing season has increased by 74.9–196.8 growing degree-days, depending on the base temperature selected. The spatial characteristics of the change in the timing and length of the growing season differ from the geographical pattern of change in temperatures over this period; but the spatial characteristics of change in growing degree-days does resemble the pattern for temperatures, with higher rates in northern regions. Nationally, two distinct regimes are evident over time: an initial period where growing season indicators fluctuate near a base period average, and a second period of rapidly increasing growing season length and thermal intensity. Growing degree-days are highly correlated with March-to-November mean air temperatures in all climatic regions of China; the length of the growing season is likewise highly correlated with March-to-November mean air temperatures except in east, southeast and southwest China at base temperature of 0°C and southeast China at base temperature of 5°C. The growing season start date appears to have the greater influence on the length of the growing season. In China, warmer growing seasons are also likely to be longer growing seasons.     

Changing Spring Phenology Dates in the Three-Rivers Headwater Region of the Tibetan Plateau during 1960–2013

The variation of the vegetation growing season in the Three-Rivers Headwater Region of the Tibetan Plateau has recently become a controversial topic. One issue is that the estimated local trend in the start of the vegetation growing season(SOS)based on remote sensing data is easily affected by outliers because this data series is short. In this study, we determine that the spring minimum temperature is the most influential factor for SOS. The significant negative linear relationship between the two variables in the region is evaluated using Moderate Resolution Imaging Spectroradiometer–Normalized Difference Vegetation Index data for 2000–13. We then reconstruct the SOS time series based on the temperature data for 1960–2013.The regional mean SOS shows an advancing trend of 1.42 d(10 yr)~(-1) during 1960–2013, with the SOS occurring on the 160th and 151st days in 1960 and 2013, respectively. The advancing trend enhances to 6.04 d(10 yr)~(-1) during the past 14 years. The spatiotemporal variations of the reconstructed SOS data are similar to those deduced from remote sensing data during the past 14 years. The latter exhibit an even larger regional mean trend of SOS [7.98 d(10 yr~(-1) )] during 2000–13. The Arctic Oscillation is found to have significantly influenced the changing SOS, especially for the eastern part of the region,during 2000–13.     

Modeling soil thermal and hydrological dynamics and changes of growing season in Alaskan terrestrial ecosystems

Abundant evidence indicates the growing season has been changed in the Alaskan terrestrial ecosystems in the last century as climate warms. Reasonable simulations of growing season length, onset, and ending are critical to a better understanding of carbon dynamics in these ecosystems. Recent ecosystem modeling studies have been slow to consider the interactive effects of soil thermal and hydrological dynamics on growing season changes in northern high latitudes. Here, we develop a coupled framework to model these dynamics and their effects on plant growing season at a daily time step. In this framework, we (1) incorporate a daily time step snow model into our existing hydrological and soil thermal models and (2) explicitly model the moisture effects on soil thermal conductivity and heat capacity and the effects of active layer depth and soil temperature on hydrological dynamics. The new framework is able to well simulate snow depth and soil temperature profiles for both boreal forest and tundra ecosystems at the site level. The framework is then applied to Alaskan boreal forest and tundra ecosystems for the period 1923–2099. Regional simulations show that (1) for the historical period, the growing season length, onset, and ending, estimated based on the mean soil temperature of the top 20 cm soils, and the annual cycle of snow dynamics, agree well with estimates based on satellite data and other approaches and (2) for the projected period, the plant growing season length shows an increasing trend in both tundra and boreal forest ecosystems. In response to the projected warming, by year 2099, (1) the snow-free days will be increased by 41.0 and 27.5 days, respectively, in boreal forest and tundra ecosystems and (2) the growing season lengths will be more than 28 and 13 days longer in boreal forest and tundra ecosystems, respectively, compared to 2010. Comparing two sets of simulations with and without considering feedbacks between soil thermal and hydrological dynamics, our analyses suggest coupling hydrological and soil thermal dynamics in Alaskan terrestrial ecosystems is important to model ecosystem dynamics, including growing season changes.     

Spatiotemporal change in the climatic growing season in Northeast China during 1960–2009

Daily mean air temperatures from 81 meteorological stations in Northeast China were analyzed for the spatiotemporal change of the climatic growing season during the period 1960–2009. Our results showed that latitude strongly influenced the spatial patterns of the mean start (GSS), end (GSE), and length (GSL) of the growing season. For the area studied, a significant increasing trend in GSL during 1960–2009 was detected at a significance level of 0.01, especially after the early 1980s. The area-average GSL has extended 13.3 days during the last 50 years, mainly due to the advanced GSS evident in the spring (7.9 days). The variations of GSS and GSE were closely correlated with the monthly mean temperature (T _mean) of April and October, respectively, while GSL was closely related to the monthly minimum temperatures (T _min) of spring (March to April) and autumn (September to October). The distributions of the trends in growing season parameters (GSS, GSE, and GSL) showed great spatial variability over Northeast China. Significant relationships between altitude and the trend rates of the GSS and GSL were detected, while geographic parameters had little direct effect on the change in GSE. This extended growing season may provide favorable conditions for agriculture and forest, and improve their potential production.     

Impacts of snow cover on vegetation phenology in the arctic from satellite data

The dynamics of snow cover is considered an essential factor in phenological changes in Arctic tundra and other northern biomes. The Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra satellite data were selected to monitor the spatial and temporal heterogeneity of vegetation phenology and the timing of snow cover in western Arctic Russia (the Yamal Peninsula) during the period 2000-10. The magnitude of changes in vegetation phenology and the timing of snow cover were highly heterogeneous across latitudinal gradients and vegetation types in western Arctic Russia. There were identical latitudinal gradients for "start of season" (SOS) (r2 = 0.982, p<0.0001), "end of season" (EOS) (r2 = 0.938, p<0.0001), and "last day of snow cover" (LSC) (r2 = 0.984, p<0.0001), while slightly weaker relationships between latitudinal gradients and "first day of snow cover" (FSC) were observed (r2 = 0.48, p<0.0042). Delayed SOS and FSC, and advanced EOS and LSC were found in the south of the region, while there were completely different shifts in the north. SOS for the various land cover features responded to snow cover differently, while EOS among different vegetation types responded to snowfall almost the same. The timing of snow cover is likely a key driving factor behind the dynamics of vegetation phenology over the Arctic tundra. The present study suggests that snow cover urgently needs more attention to advance understanding of vegetation phenology in the future.     

中亚及中国新疆干旱区植被物候时空变化

基于1982-2006年GIMMS（Global Inventory Modeling and Mapping Studies）长序列归一化植被指数数据,采用比例阈值法反演得到中亚及新疆地区植被过去25年的物候数据集;采用M-K趋势检验和Theil Sen斜率方法,分析植物生长季开始期、停止期和生长季长度的变化趋势,并结合历史土地利用数据和DEM数据评价不同植被覆盖类型和不同高程下的植被物候变化特征。结果表明：1982-2006年,中亚及中国新疆干旱区植被生长季开始期和停止期在区域尺度上没有显著提前或者延迟,但在局部地区变化明显,且空间差异较大。各植被覆盖类型的物候动态表现不同,农用地的生长季开始期提前最明显;落叶阔叶林等木本植被类型的生长季停止期以推迟为主,但其面积比例很小,影响十分有限;除灌丛和裸地外,其他类型均表现出生长季长度延长的趋势,但整个研究区植物生长季长度变化并不明显。不同高程下植被物候变化同样存在差异,区域气候变化改变了不同高程带的环境限制因子,继而对植被物候产生影响,特别是在2000～3000 m高程带,植被生长季开始期提前、停止期推迟和生长季长度延长更加明显。     

The contribution of snow condition trends to future ground climate

Global climate models predict that terrestrial northern high-latitude snow conditions will change substantially over the twenty-first century. Results from a Community Climate System Model simulation of twentieth and twenty-first (SRES A1B scenario) century climate show increased winter snowfall (+10–40%), altered maximum snow depth (?5 ± 6 cm), and a shortened snow-season (?14 ± 7 days in spring, +20 ± 9 days in autumn). By conducting a series of prescribed snow experiments with the Community Land Model, we isolate how trends in snowfall, snow depth, and snow-season length affect soil temperature trends. Increasing snowfall, by countering the snowpack-shallowing influence of warmer winters and shorter snow seasons, is effectively a soil warming agent, accounting for 10–30% of total soil warming at 1 m depth and ~16% of the simulated twenty-first century decline in near-surface permafrost extent. A shortening snow season enhances soil warming due to increased solar absorption whereas a shallowing snowpack mitigates soil warming due to weaker winter insulation from cold atmospheric air. Snowpack deepening has comparatively less impact due to saturation of snow insulative capacity at deeper snow depths. Snow depth and snow-season length trends tend to be positively related, but their effects on soil temperature are opposing. Consequently, on the century timescale the net change in snow state can either amplify or mitigate soil warming. Snow state changes explain less than 25% of total soil temperature change by 2100. However, for the latter half of twentieth century, snow state variations account for as much as 50–100% of total soil temperature variations.     

Temperature and thermal growing season variations along elevational gradients on a sub-alpine,temperate China

Fully and accurately studying temperature variations in montane areas are conducive to a better understanding of climate modeling and climate-growth relationships on regional scales. To explore the spatio-temporal changes in air and soil temperatures and their relationship in montane areas, on-site monitoring over 2 years (2015 and 2016) was conducted at nine different elevations from 2040 to 2740 m a.s.l. on Luya Mountain in the semiarid region of China. The results showed that the annual mean of air temperature lapse rate (ATLR) was 0.67 °C/100 m. ATLR varied obviously in different months within a range of 0.57~0.79 °C/100 m. The annual mean of the soil temperature lapse rate (STLR) was 0.48 °C/100 m. Seasonally, monthly mean soil temperature did not show a consistent pattern with regard to elevation. The relationships between air and soil temperatures showed piecewise changes. Soil was decoupled from the air temperature in cold winter and early spring. The parameters of the growing season based on the two temperature types had no corresponding relations, and seasonal mean of soil temperature showed the smallest value at mid-elevation rather than in the treeline ecotone. Based on these changes, our results emphasized that altitudinal and seasonal variability caused by local factors (such as snow cover and soil moisture) should be taken into full consideration in microclimate extrapolation and treeline prediction in montane areas, especially in relation to soil temperature.     

Climate change in Bangladesh: a spatio-temporal analysis and simulation of recent temperature and rainfall data using GIS and time series analysis model

In this paper, temperature and rainfall data series were analysed from 34 meteorological stations distributed throughout Bangladesh over a 40-year period (1971 to 2010) in order to evaluate the magnitude of these changes statistically and spatially. Linear regression, coefficient of variation, inverse distance weighted interpolation techniques and geographical information systems were performed to analyse the trends, variability and spatial patterns of temperature and rainfall. Autoregressive integrated moving average time series model was used to simulate the temperature and rainfall data. The results confirm a particularly strong and recent climate change in Bangladesh with a 0.20 °C per decade upward trend of mean temperature. The highest upward trend in minimum temperature (range of 0.80–2.4 °C) was observed in the northern, northwestern, northeastern, central and central southern parts while greatest warming in the maximum temperature (range of 1.20–2.48 °C) was found in the southern, southeastern and northeastern parts during 1971–2010. An upward trend of annual rainfall (+7.13 mm per year) and downward pre-monsoon (?0.75 mm per year) and post-monsoon rainfall (?0.55 mm per year) trends were observed during this period. Rainfall was erratic in pre-monsoon season and even more so during the post-monsoon season (variability of 44.84 and 85.25 % per year, respectively). The mean forecasted temperature exhibited an increase of 0.018 °C per year in 2011–2020, and if this trend continues, this would lead to approximately 1.0 °C warmer temperatures in Bangladesh by 2020, compared to that of 1971. A greater rise is projected for the mean minimum (0.20 °C) than the mean maximum (0.16 °C) temperature. Annual rainfall is projected to decline 153 mm from 2011 to 2020, and a drying condition will persist in the northwestern, western and southwestern parts of the country during the pre- and post-monsoonal seasons.     

1982-2012年北半球荒漠草原过渡带植被物候特征及其与气候因子的关系

基于GIMMS（global inventory modeling and mapping studies）NDVI 3g数据,在提取北半球荒漠草原过渡带每年植被物候期的基础上,研究了1982-2012年物候期的时间演化趋势及空间分异特征,并结合全球气候再分析资料,探讨了物候变化的气候驱动因素。结果表明：在1998年之前,荒漠草原过渡带植被物候期变化地区间差异较大,而在1998年之后,北半球荒漠草原过渡带生长季结束期整体提前,平均提前0.41 d/a;同时,除萨赫勒以外的各地区植被生长季长度普遍缩短,平均缩短0.88 d/a。植被物候期与气候因子的相关分析发现,荒漠草原过渡带植被物候变化受气候变化影响显著,且空间差异明显。在中高纬度地区,气温是限制植被活动的关键因子,温度升高可以促进生长季开始期的提前,而降水增加则会妨碍植被生长;在较低纬度地区,水分是影响植被活动的关键因素,高温造成的水分亏缺会导致植被生长季缩短。从植被物候期对各气候因子响应的时滞性来看,荒漠草原过渡带植被的物候期对气温变化的响应最迅速,对蒸散的响应存在一定的滞后性,而对降水的响应不存在时滞差异。     

Changes in Canada's Climate: Trends in Indices Based on Daily Temperature and Precipitation Data

ABSTRACT

Trends in indices based on daily temperature and precipitation are examined for two periods: 1948–2016 for all stations in Canada and 1900–2016 for stations in the south of Canada. These indices, a number of which reflect extreme events, are considered to be impact relevant. The results show changes consistent with warming, with larger trends associated with cold temperatures. The number of summer days (when daily maximum temperature >25°C) has increased at most locations south of 65°N, and the number of hot days (daily maximum temperature >30°C) and hot nights (daily minimum temperature >22°C) have increased at a few stations in the most southerly regions. Very warm temperatures in both summer and winter (represented by the 95th percentile of their daily maximum and minimum temperatures, respectively) have increased across the country, with stronger trends in winter. Warming is more pronounced for cold temperatures. The frost-free season has become longer with fewer frost days, consecutive frost days, and ice days. Very cold temperatures in both winter and summer (represented by the 5th percentile of their daily maximum and minimum temperatures, respectively) have increased substantially across the country, again with stronger trends in the winter. Changes in other temperature indices are consistent with warming. The growing season is now longer, and the number of growing degree-days has increased. The number of heating degree-days has decreased across the country, while the number of cooling degree-days has increased at many stations south of 55°N. The frequency of annual and spring freeze–thaw days shows an increase in the interior provinces and a decrease in the remainder of the country. Changes in precipitation indices are less spatially coherent. An increase in the number of days with rainfall and heavy rainfall is found at several locations in the south. A decrease in the number of days with snowfall and heavy snowfall is observed in the western provinces, while an increase is found in the north. There is no evidence of significant changes in the annual highest 1-day rainfall and 1-day snowfall. The maximum number of consecutive dry days has decreased, mainly in the south.     

Soil thermal dynamics of terrestrial ecosystems of the conterminous United States from 1948 to 2008: an analysis with a process-based soil physical model and AmeriFlux data

The spatiotemporal distribution characteristics of soil temperature are a significant, but seldom described signal of climate warming. This study examines the spatiotemporal trends in soil temperature at depths of 10, 20, and 50 cm in the conterminous US during 1948–2008. We find a warming trend of between 0.2 and 0.4 °C at all depths from 1948 to 2008. The lowest soil temperatures are in Colorado and the area where Wyoming, Idaho, and Montana meet. The coastal areas, such as Texas, Florida, and California, experienced the highest soil temperature. In addition, areas that experienced weak cooling in summer soil temperature include Texas, Oklahoma, and Arkansas. Warming was recorded in Arizona, Nevada, and Oregon. In winter, Mississippi, Alabama, and Georgia show a cooling trend, and Montana, North Dakota, and South Dakota have been warming over the 61-year period. Additionally, mix-forest areas experience slightly cooler soil temperature in comparison with air temperature. Shrubland areas experience slightly warmer soil temperature in comparison with air temperature. This study is among the first to analyze the spatiotemporal distribution characteristics of soil temperature in the conterminous US by using multiple site observational data. Improved understanding of the spatially complex responses of soil temperature shall have significant implications for future studies in climate change over the region.     

The 20th century cooling trend over the southeastern United States

Portions of the southern and southeastern United States, primarily Mississippi, Alabama, and Georgia, have experienced century-long (1895–2007) downward air temperature trends that occur in all seasons. Superimposed on them are shifts in mean temperatures on decadal scales characterized by alternating warm (1930s–1940s, 1990s) and cold (1900s; 1960s–1970s) regimes. Regional atmospheric circulation and SST teleconnection indices, station-based cloud cover and soil moisture (Palmer drought severity index) data are used in stepwise multiple linear regression models. These models identify predictors linked to observed winter, summer, and annual Southeastern air temperature variability, the observed variance (r²) they explain, and the resulting prediction and residual time series. Long-term variations and trends in tropical Pacific sea temperatures, cloud cover, soil moisture and the North Atlantic and Arctic oscillations account for much of the air temperature downtrends. Soil moisture and cloud cover are the primary predictors of 59.6 % of the observed summer temperature variance. While the teleconnections, cloud cover and moisture data account for some of the annual and summer Southeastern cooling trend, large significant downward trending residuals remain in winter and summer. Comparison is made to the northeastern United States where large twentieth century upward air temperature trends are driven by cloud cover increases and Atlantic Multidecadal Oscillation (AMO) variability. Differences between the Northeastern warming and the Southeastern cooling trends in summer are attributable in part to the differing roles of cloud cover, soil moisture, the Arctic Oscillation and the AMO on air temperatures of the 2 regions.