Characterization and Analysis of Hailstorms in the Northern Great Plains

Hail is a meteorological occurrence that appears frequently during spring and summer across the Northern Great Plains. This paper first characterizes patterns associated with reported hail events occurring within a five-state region (North Dakota, Minnesota, South Dakota, Iowa, and Nebraska) from 2000-2006 using records taken from the National Climatic Data Center (NCDC) Severe Storms database. Patterns of interest include the seasonality of hail activity for each state and across the region, observational bias in the reporting of hailstone size, and temporal trends in the number of hail reports across the region and in each state. This paper then explores a possible link between the solar cycle and regional hail activity. Daily observations of solar radio flux (at 10.7 cm) and National Weather Service hail reports dating from 1956-2006 were compared. A chi-squared goodness of fit analyses showed possible associations exhibiting weaker significance in Solar Cycles (S.C.) 21 and 22, and higher significance during S.C. 23. The recent appearance of a significant linkage may be due to changes in reporting effort, weather patterns, or both. Further study is required to distinguish observational artifacts from geophysical effects. Because hail activity is common to the Northern Great Plains, a deeper understanding of the effects of the solar cycle on hail and also the spatial and temporal patterns associated with regional hail may prove beneficial for climate prediction, weather forecasting, and underwriting of crop-hail insurance

Reanalysis Data Underestimate Significant Changes in Growing Season Weather in Kazakhstan

We present time series analyses of recently compiled climate station data which allowed us to assess contemporary trends in growing season weather across Kazakhstan as drivers of a significant decline in growing season normalized difference vegetation index (NDVI) recently observed by satellite remote sensing across much of Central Asia. We used a robust nonparametric time series analysis method, the seasonal Kendall trend test to analyze georeferenced time series of accumulated growing season precipitation (APPT) and accumulated growing degree-days (AGDD). Over the period 2000–2006 we found geographically extensive, statistically significant (p \u3c 0.05) decreasing trends in APPT and increasing trends in AGDD. The temperature trends were especially apparent during the warm season and coincided with precipitation decreases in northwest Kazakhstan, indicating that pervasive drought conditions and higher temperature excursions were the likely drivers of NDVI declines observed in Kazakhstan over the same period. We also compared the APPT and AGDD trends at individual stations with results from trend analysis of gridded monthly precipitation data from the Global Precipitation Climatology Centre (GPCC) Full Data Reanalysis v4 and gridded daily near surface air temperature from the National Centers for Climate Prediction Reanalysis v2 (NCEP R2). We found substantial deviation between the station and the reanalysis trends, suggesting that GPCC and NCEP data substantially underestimate the geographic extent of recent drought in Kazakhstan. Although gridded climate products offer many advantages in ease of use and complete coverage, our findings for Kazakhstan should serve as a caveat against uncritical use of GPCC and NCEP reanalysis data and demonstrate the importance of compiling and standardizing daily climate data from data-sparse regions like Central Asia

Assessing Long-Term Trends In Vegetation Productivity Change Over the Bani River Basin in Mali (West Africa)

Using time series of Normalized Difference Vegetation Index (NDVI) and rainfall data, we investigated historical vegetation productivity trends from 1982 to 2011 over the Bani River Basin in Mali. Statistical agreements between long-term trends in vegetation productivty, corresponding rainfall and rate of land cover change from Landsat time-series imagery was used to discern climate versus human-induced vegetation cover change. Spearman correlation was used to investigate the relationship between metrics of vegetation, rainfall trends and land cover change categories. The results show there is a positive correlation between increases in rainfall and some land cover classes, while some classes such as settlements were negatively correlated with vegetation productivity trends. Croplands and Natural Vegetation were positively correlated (r=0.89) with rainfall while settlements have a negative correlation with NDVI time series trend (r=-057). Despite the fact that rainfall is the major determinant of vegetation cover dynamics in the study area, it appears that other human-induced factors such as urbanization have negatively influenced the change in vegetation cover in the study area. The results show that a combined analysis of NDVI, rainfall and spatially explicit land cover change provides a comprehensive insight into the drivers of vegetation cover change in semi-arid Africa

Change and Persistence in Land Surface Phenologies of the Don and Dnieper River Basins

The formal collapse of the Soviet Union at the end of 1991 produced major socio-economic and institutional dislocations across the agricultural sector. The picture of broad scale patterns produced by these transformations continues to be discovered. We examine here the patterns of land surface phenology (LSP) within two key river basins—Don and Dnieper—using AVHRR (Advanced Very High Resolution Radiometer) data from 1982 to 2000 and MODIS (Moderate Resolution Imaging Spectroradiometer) data from 2001 to 2007. We report on the temporal persistence and change of LSPs as summarized by seasonal integration of NDVI (normalized difference vegetation index) time series using accumulated growing degree-days (GDDI NDVI). Three land cover super-classes—forest lands, agricultural lands, and shrub lands—constitute 96% of the land area within the basins. All three in both basins exhibit unidirectional increases in AVHRR GDDI NDVI between the Soviet and post-Soviet epochs. During the MODIS era (2001–2007), different socio-economic trajectories in Ukraine and Russia appear to have led to divergences in the LSPs of the agricultural lands in the two basins. Interannual variation in the shrub lands of the Don river basin has increased since 2000. This is due in part to the better signal-to-noise ratio of the MODIS sensor, but may also be due to a regional drought affecting the Don basin more than the Dnieper basin

Evapotranspiration in the Nile Basin: Identifying Dynamics, Trends, and Drivers 2002-2011

Analysis of the relationship between evapotranspiration (ET) and its natural and anthropogenic drivers is critical in water-limited basins such as the Nile. The spatiotemporal relationships of ET with rainfall and vegetation dynamics in the Nile Basin during 2002–2011 were analyzed using satellite-derived data. Non-parametric statistics were used to quantify ET-rainfall interactions and trends across land cover types and subbasins. We found that 65% of the study area (2.5 million km2) showed significant (p \u3c 0.05) positive correlations between monthly ET and rainfall, whereas 7% showed significant negative correlations. As expected, positive ET-rainfall correlations were observed over natural vegetation, mixed croplands/natural vegetation, and croplands, with a few subbasin-specific exceptions. In particular, irrigated croplands, wetlands and some forests exhibited negative correlations. Trend tests revealed spatial clusters of statistically significant trends in ET (6% of study area was negative; 12% positive), vegetation greenness (24% negative; 12% positive) and rainfall (11% negative; 1% positive) during 2002–2011. The Nile Delta, Ethiopian highlands and central Uganda regions showed decline in ET while central parts of Sudan, South Sudan, southwestern Ethiopia and northeastern Uganda showed increases. Except for a decline in ET in central Uganda, the detected changes in ET (both positive and negative) were not associated with corresponding changes in rainfall. Detected declines in ET in the Nile delta and Ethiopian highlands were found to be attributable to anthropogenic land degradation, while the ET decline in central Uganda is likely caused by rainfall reduction

Changing Snow Seasonality in the Highlands of Kyrgyzstan

Few studies have examined changing snow seasonality in Central Asia. Here, we analyzed changes in the seasonality of snow cover across Kyrgyzstan (KGZ) over 14 years from 2002/03–2015/16 using the most recent version (v006) of MODIS Terra and Aqua 8 day snow cover composites (MOD10A2/MYD10A2). We focused on three metrics of snow seasonality—first date of snow, last date of snow, and duration of snow season—and used nonparametric trends tests to assess the significance and direction of trends. We evaluated trends at three administration scales and across elevation. We used two techniques to assure that our identification of significant trends was not resulting from random spatial variation. First, we report only significant trends (positive or negative) that are at least twice as prevalent as the converse trends. Second, we use a two-stage analysis at the national scale to identify asymmetric directional changes in snow seasonality. Results show that more territory has been experiencing earlier onset of snow than earlier snowmelt, and roughly equivalent areas have been experiencing longer and shorter duration of snow seasons in the past 14 years. The changes are not uniform across KGZ, with significant shifts toward earlier snow arrival in western and central KGZ and significant shifts toward earlier snowmelt in eastern KGZ. The duration of the snow season has significantly shortened in western and eastern KGZ and significantly lengthened in northern and southwestern KGZ. Duration is significantly longer where the snow onset was significantly earlier or the snowmelt significantly later. There is a general trend of significantly earlier snowmelt below 3400 m and the area of earlier snowmelt is 15 times greater in eastern than western districts. Significant trends in the Aqua product were less prevalent than in the Terra product, but the general trend toward earlier snowmelt was also evident in Aqua data

Long-term satellite NDVI data sets: evaluating their ability to detect ecosystem functional changes in South America

In the last decades, South American ecosystems underwent important functional modifications due to climate alterations and direct human intervention on land use and land cover. Among remotely sensed data sets, NOAA-AVHRR "Normalized Difference Vegetation Index" (NDVI) represents one of the most powerful tools to evaluate these changes thanks to their extended temporal coverage. In this paper we explored the possibilities and limitations of three commonly used NOAA-AVHRR NDVI series (PAL, GIMIMS and FASIR) to detect ecosystem functional changes in the South American continent. We performed pixel-based linear regressions for four NDVI variables (average annual, maximum annual, minimum annual and intra-annual coefficient of variation) for the 1982-1999 period and (1) analyzed the convergences and divergences of significant multi-annual trends identified across all series, (2) explored the degree of aggregation of the trends using the O-ring statistic, and (3) evaluated observed trends using independent information on ecosystem functional changes in five focal regions. Several differences arose in terms of the patterns of change (the sign, localization and total number of pixels with changes). FASIR presented the highest proportion of changing pixels (32.7%) and GIMMS the lowest (16.2%). PAL and FASIR data sets showed the highest agreement, with a convergence of detected trends on 71.2% of the pixels. Even though positive and negative changes showed substantial spatial aggregation, important differences in the scale of aggregation emerged among the series, with GIMMS showing the smaller scale (11 pixels). The independent evaluations suggest higher accuracy in the detection of ecosystem changes among PAL and FASIR series than with GIMMS, as they detected trends that match expected shifts. In fact, this last series eliminated most of the long term patterns over the continent. For example, in the "Eastern Paraguay" and "Uruguay River margins" focal regions, the extensive changes due to land use and land cover change expansion were detected by PAL and FASIR, but completely ignored by GIMMS. Although the technical explanation of the differences remains unclear and needs further exploration, we found that the evaluation of this type of remote sensing tools should not only be focused at the level of assumptions (i.e. physical or mathematical aspects of image processing), but also at the level of results (i.e. contrasting observed patterns with independent proofs of change). We finally present the online collaborative initiative "Land ecosystem change utility for South America", which facilitates this type of evaluations and helps to identify the most important functional changes of the continent.Fil: Baldi, Germán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Nosetto, Marcelo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Aragón, Myriam Roxana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentina. Universidad de Buenos Aires. Facultad de Agronomía; ArgentinaFil: Aversa, Fernando. Universidad Nacional de San Luis; ArgentinaFil: Paruelo, José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Jobbagy Gampel, Esteban Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentin

Climate Change, Growing Season Water Deficit And Vegetation Activity Along The North-South Transect Of Eastern China From 1982 Through 2006

Considerable work has been done to examine the relationship between environmental constraints and vegetation activities represented by the remote sensing-based normalized difference vegetation index (NDVI). However, the relationships along either environmental or vegetational gradients are rarely examined. The aim of this paper was to identify the vegetation types that are potentially susceptible to climate change through examining their interactions between vegetation activity and evaporative water deficit. We selected 12 major vegetation types along the north–south transect of eastern China (NSTEC), and tested their time trends in climate change, vegetation activity and water deficit during the period 1982–2006. The result showed significant warming trends accompanied by general precipitation decline in the majority of vegetation types. Despite that the whole transect increased atmospheric evaporative demand (ET<sub>0</sub>) during the study period, the actual evapotranspiration (ET<sub>a</sub>) showed divergent trends with ET<sub>0</sub> in most vegetation types. Warming and water deficit exert counteracting controls on vegetation activity. Our study found insignificant greening trends in cold temperate coniferous forest (CTCF), temperate deciduous shrub (TDS), and three temperate herbaceous types including the meadow steppe (TMS), grass steppe (TGS) and grassland (TG), where warming exerted more effect on NDVI than offset by water deficit. The increasing growing season water deficit posed a limitation on the vegetation activity of temperate coniferous forest (TCF), mixed forest (TMF) and deciduous broad-leaved forest (TDBF). Differently, the growing season brownings in subtropical or tropical forests of coniferous (STCF), deciduous broad-leaved (SDBF), evergreen broad-leaved (SEBF) and subtropical grasslands (STG) were likely attributed to evaporative energy limitation. The growing season water deficit index (GWDI) has been formulated to assess ecohydrological equilibrium and thus indicating vegetation susceptibility to water deficit. The increasing GWDI trends in CTCF, TCF, TDS, TG, TGS and TMS indicated their rising susceptibility to future climate change

Climate change, growing season water deficit and vegetation activity along the north–south transect of eastern China from 1982 through 2006

Considerable work has been done to examine the relationship between environmental constraints and vegetation activities represented by the remote sensing-based normalized difference vegetation index (NDVI). However, the relationships along either environmental or vegetational gradients are rarely examined. The aim of this paper was to identify the vegetation types that are potentially susceptible to climate change through examining their interactions between vegetation activity and evaporative water deficit. We selected 12 major vegetation types along the north–south transect of eastern China (NSTEC), and tested their time trends in climate change, vegetation activity and water deficit during the period 1982–2006. The result showed significant warming trends accompanied by general precipitation decline in the majority of vegetation types. Despite that the whole transect increased atmospheric evaporative demand (ET0) during the study period, the actual evapotranspiration (ETa) showed divergent trends with ET0 in most vegetation types. Warming and water deficit exert counteracting controls on vegetation activity. Our study found insignificant greening trends in cold temperate coniferous forest (CTCF), temperate deciduous shrub (TDS), and three temperate herbaceous types including the meadow steppe (TMS), grass steppe (TGS) and grassland (TG), where warming exerted more effect on NDVI than offset by water deficit. The increasing growing season water deficit posed a limitation on the vegetation activity of temperate coniferous forest (TCF), mixed forest (TMF) and deciduous broad-leaved forest (TDBF). Differently, the growing season brownings in subtropical or tropical forests of coniferous (STCF), deciduous broad-leaved (SDBF), evergreen broad-leaved (SEBF) and subtropical grasslands (STG) were likely attributed to evaporative energy limitation. The growing season water deficit index (GWDI) has been formulated to assess ecohydrological equilibrium and thus indicating vegetation susceptibility to water deficit. The increasing GWDI trends in CTCF, TCF, TDS, TG, TGS and TMS indicated their rising susceptibility to future climate change

A Multitemporal Analysis of Georgia\u27s Coastal Vegetation, 1990-2005

Land and vegetation changes are part of the continuous and dynamic cycle of earth system variation. This research examines vegetation changes in the 21-county eco-region along coastal Georgia. The Advanced Very High Resolution Radiometer (AVHRR) with Normalized Difference Vegetation Index (NDVI) data is used in tandem with a Principal Component Analysis (PCA) and climatic variables to determine where, and to what extent vegetation and land cover change is occurring. This research is designed around a 16 year time-series from 1990-2005. Findings were that mean NDVI values were either steady or slightly improved, and that PC1 (Healthiness) and PC2 (Time-Change) explained nearly 99 percent of the total mean variance. Healthiness declines are primarily the result of expanding urban districts and decreased soil moisture while increases are the results of restoration, and increased soil moisture. This research aims to use this analysis for the assessment of land changes as the conduit for future environmental research