Spatiotemporal Mapping of Temperature and Precipitation for the Development of a Multidecadal Climatic Dataset for Wisconsin

2009 ◽  
Vol 48 (4) ◽  
pp. 742-757 ◽  
Author(s):  
Shawn P. Serbin ◽  
Christopher J. Kucharik
Keyword(s):  
Daily Precipitation ◽  
Regional Scale ◽  
Forest Products ◽  
The State ◽  
Maximum Temperature ◽  
Monthly Precipitation ◽  
Moderate Degree ◽  
Temperature And Precipitation ◽  
Gridded Dataset ◽  
Interpolation Accuracy

Abstract Results from the generation of a multidecadal gridded climatic dataset for 57 yr (1950–2006) of daily and monthly precipitation (PTotal), maximum temperature (Tmax), and minimum temperature (Tmin) are presented for the important agricultural and forest products state of Wisconsin. A total of 176 climate stations were used in the final gridded dataset that was constructed at 8-km (5.0′) latitude–longitude resolution using an automated inverse distance weighting interpolation. Accuracy statistics for the interpolated data were based on a rigorous validation step using 104 first- and second-order climate observation stations withheld in the production of the gridded dataset. The mean absolute errors (MAE) for daily minimum and maximum temperatures averaged 1.51° and 1.31°C, respectively. Daily precipitation errors were also reasonable, ranging from −0.04 to 0.08 mm, on average, across all climate divisions in the state with an overall statewide MAE of 1.37 mm day−1. Correlation analysis suggested a high degree of explained variation for daily temperature (R2 ≥ 0.97) and a moderate degree for daily precipitation (R2 = 0.66), whereby the realism improved considerably for monthly precipitation accumulation totals (R2 = 0.87). Precipitation had the best interpolation accuracy during the winter months, related to large-scale, synoptic weather systems, and accuracy was at a minimum in the wetter summer months when more precipitation originates from local-to-regional-scale convective forcing. Overall the grids showed coherent spatial patterns in temperature and precipitation that were expected for this region, such as the latitudinal gradient in temperature and longitudinal gradient in precipitation across the state. The grids will prove useful for a variety of regional-scale research and ecosystem modeling studies.

scholarly journals North American historical monthly spatial climate dataset, 1901–2016

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Heather MacDonald ◽  
Daniel W. McKenney ◽  
Pia Papadopol ◽  
Kevin Lawrence ◽  
John Pedlar ◽  
...  
Keyword(s):  
North American ◽  
Minimum Temperature ◽  
Cross Validation ◽  
Spatial Models ◽  
Maximum Temperature ◽  
Monthly Precipitation ◽  
Prediction Errors ◽  
The North ◽  
Temperature And Precipitation ◽  
Predictive Error

AbstractWe present historical monthly spatial models of temperature and precipitation generated from the North American dataset version “j” from the National Oceanic and Atmospheric Administration’s (NOAA’s) National Centres for Environmental Information (NCEI). Monthly values of minimum/maximum temperature and precipitation for 1901–2016 were modelled for continental United States and Canada. Compared to similar spatial models published in 2006 by Natural Resources Canada (NRCAN), the current models show less error. The Root Generalized Cross Validation (RTGCV), a measure of the predictive error of the surfaces akin to a spatially averaged standard predictive error estimate, averaged 0.94 °C for maximum temperature models, 1.3 °C for minimum temperature and 25.2% for total precipitation. Mean prediction errors for the temperature variables were less than 0.01 °C, using all stations. In comparison, precipitation models showed a dry bias (compared to recorded values) of 0.5 mm or 0.7% of the surface mean. Mean absolute predictive errors for all stations were 0.7 °C for maximum temperature, 1.02 °C for minimum temperature, and 13.3 mm (19.3% of the surface mean) for monthly precipitation.

A model for predicting human-caused wildfire occurrence in the region of Madrid, Spain

2010 ◽  
Vol 19 (3) ◽  
pp. 325 ◽  
Author(s):  
Lara Vilar ◽  
Douglas. G. Woolford ◽  
David L. Martell ◽  
M. Pilar Martín
Keyword(s):  
Regional Scale ◽  
Additive Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Generalised Additive Model ◽  
Wildfire Occurrence ◽  
Temperature And Precipitation ◽  
Spatio Temporal ◽  
Development And Validation

This paper describes the development and validation of a spatio-temporal model for human-caused wildfire occurrence prediction at a regional scale. The study area is the 8028-km2 region of Madrid, located in central Spain, where more than 90% of wildfires are caused by humans. We construct a logistic generalised additive model to estimate daily fire ignition risk at a 1-km2 grid spatial resolution. Spatially referenced socioeconomic and weather variables appear as covariates in the model. Spatial and temporal effects are also included. The variables in the model were selected using an iterative approach, which we describe. We use the model to predict the expected number of fires in our study area during the 2002–05 period, by aggregating the estimated probabilities over space–time scales of interest. The estimated partial effects of the presence of railways, roads, and wildland–urban interface in forest areas were highly significant, as were the observed daily maximum temperature and precipitation.

scholarly journals Evolution and characteristics of frequency, duration and magnitude of drought events in the central Pyrenees since 1940

2021 ◽  
Author(s):  
Javier Sigro
Keyword(s):  
Regional Climate ◽  
Maximum Temperature ◽  
Monthly Precipitation ◽  
Maximum Magnitude ◽  
Standardized Precipitation Evapotranspiration Index ◽  
Data Set ◽  
Eastern Pyrenees ◽  
Temperature And Precipitation ◽  
Number Magnitude ◽  
Central Pyrenees

<p>The central sectors of the Pyrenees have experienced a significant increase in the average and extreme daily temperature during the last 80 years, as well as a downward trend in precipitation totals (Perez-Zanón et al., 2016). This article addresses the evolution of the number, magnitude and duration of drought events in the Spanish Central Pyrenees from 8 decades of temperature and precipitation records integrated into the high-quality Central Pyrenees data set (Perez-Zanón et al., 2016 ), using the Standardised Precipitation-Evapotranspiration Index (SPEI) index (Begueria et al., 2014; Vicente-Serrano et al., 2010). Series of monthly mean temperature, monthly maximum temperature, monthly minimum temperature and accumulated monthly precipitation corresponding to 15 quality controlled and homogeneity adjusted meteorological observatories have been used. This index has been calculated for 3, 6, 12 and 24 months, in order to analyse its behaviour ​​for different types of drought.</p><p>The analysis of SPEI index series indicates a tendency to increase in the frequency of drought events and in their maximum magnitude in the 4 time scales of the SPEI index analysed, especially since the 1980s. This increase in the number of events is also accompanied by an increase in their duration, especially in the case of SPEI3 and SPEI6, although not in the case of SPEI12 and SPEI24</p><p>The spatial patterns calculated from the series of the indices also show a clear east-west pattern differentiated between the index signal for the eastern Pyrenees and the western Pyrenees.</p><p>REFERENCES</p><p>Beguería, S., Vicente-Serrano, S.M., Fergus Reig, Borja Latorre. Standardized Precipitation Evapotranspiration Index (SPEI) revisited (2014): parameter fitting, evapotranspiration models, kernel weighting, tools, datasets and drought monitoring. International Journal of Climatology, 34: 3001-3023</p><p>Pérez-Zanón, N., Sigró, J. and Ashcroft, L. (2016), Temperature and precipitation regional climate series over the central Pyrenees during 1910–2013. Int. J. Climatol. DOI:10.1002/joc.4823</p><p>Vicente-Serrano S.M., Santiago Beguería, Juan I. López-Moreno, (2010) A Multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index - SPEI. Journal of Climate 23: 1696-1718.</p>

scholarly journals Temporal Patterns of the Two-Dimensional Spatial Trends in Summer Temperature and Monsoon Precipitation of Bangladesh

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Avit Kumar Bhowmik
Keyword(s):  
Regional Scale ◽  
Temporal Patterns ◽  
Least Square ◽  
Maximum Temperature ◽  
Climate Indices ◽  
Two Dimensional ◽  
Monsoon Precipitation ◽  
The North ◽  
Temperature And Precipitation ◽  
Spatial Trends

Two climate indices, TXx and PRCPTOT, representing the summer maximum temperature and annual total monsoon precipitation, respectively, in Bangladesh were computed. The temperature and precipitation measurements from 34 meteorological stations during the temporal extent of 1948–2007 were applied for indices’ computation under thorough quality control. The spatial trends of the indices were analyzed by applying two-dimensional least square approach along latitudes and longitudes of the observation points. The temporal patterns of the spatial trends were identified by temporally interpolating them applying thin plate smoothing spline method. The analyses of TXx identified regional scale spatial trends in the east-west and south-north directions, which were increasing between 1948 and 1980s. After the 1980s the spatial trends started decreasing, and after 2000 the spatial trend along the south-north changed its direction to the north-south and continued until present. The analyses of the PRCPTOT identified spatial trends in the west-east and north-south directions, which were decreasing between 1948 and 1980s and thereafter increasing until present. About half of the spatial trends were significant in F-statistics at or more than 90% confidence level. Thus, the obtained results indicated a significant climatic shift within the regional scale of the country during the study period.

An Update on Trends in Skill of Daily Forecasts of Temperature and Precipitation at the State University of New York at Albany

1983 ◽  
Vol 64 (4) ◽  
pp. 346-354 ◽  
Author(s):  
Lance F. Bosart
Keyword(s):  
New York ◽  
Minimum Temperature ◽  
Linear Regression Analysis ◽  
Precipitation Amount ◽  
The State ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
State University ◽  
Skill Levels ◽  
Temperature And Precipitation

Consensus (the average of all forecasts) skill levels in forecasting daily maximum and minimum temperature, precipitation probability across six class intervals, and precipitation amount at the State University of New York at Albany are reviewed for the period 1977–82. Skill is measured relative to a climatological control. Forecasts are made for four consecutive 24 h periods for Albany, N.Y., beginning at 1800 GMT of the current day. For minimum temperature, the skill levels average 57%, 41%, 26%, and 15%, respectively, for 24, 48, 72, and 96 h in advance. For maximum temperature, a more limited sample yields corresponding skill levels of 84%, 49%, 34%, and 19% for 12, 36, 60, 84 h ahead. Linear regression analysis yields little in the way of a definitive trend, given the smallness of the explained variance. Comparison with other readily available objective and subjective operational guidance establishes the credibility of the consensus forecast.

scholarly journals Projected Changes in Climate Extremes Using CMIP6 Simulations Over SREX Regions

2021 ◽  
Vol 5 (3) ◽  
pp. 481-497
Author(s):  
Mansour Almazroui ◽  
Fahad Saeed ◽  
Sajjad Saeed ◽  
Muhammad Ismail ◽  
Muhammad Azhar Ehsan ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Extreme Events ◽  
First Century ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
Temperature And Precipitation ◽  
Projected Change ◽  
Twenty First Century ◽  
Projected Changes ◽  
The Tropics

AbstractThis paper presents projected changes in extreme temperature and precipitation events by using Coupled Model Intercomparison Project phase 6 (CMIP6) data for mid-century (2036–2065) and end-century (2070–2099) periods with respect to the reference period (1985–2014). Four indices namely, Annual maximum of maximum temperature (TXx), Extreme heat wave days frequency (HWFI), Annual maximum consecutive 5-day precipitation (RX5day), and Consecutive Dry Days (CDD) were investigated under four socioeconomic scenarios (SSP1-2.6; SSP2-4.5; SSP3-7.0; SSP5-8.5) over the entire globe and its 26 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions. The projections show an increase in intensity and frequency of hot temperature and precipitation extremes over land. The intensity of the hottest days (as measured by TXx) is projected to increase more in extratropical regions than in the tropics, while the frequency of extremely hot days (as measured by HWFI) is projected to increase more in the tropics. Drought frequency (as measured by CDD) is projected to increase more over Brazil, the Mediterranean, South Africa, and Australia. Meanwhile, the Asian monsoon regions (i.e., South Asia, East Asia, and Southeast Asia) become more prone to extreme flash flooding events later in the twenty-first century as shown by the higher RX5day index projections. The projected changes in extremes reveal large spatial variability within each SREX region. The spatial variability of the studied extreme events increases with increasing greenhouse gas concentration (GHG) and is higher at the end of the twenty-first century. The projected change in the extremes and the pattern of their spatial variability is minimum under the low-emission scenario SSP1-2.6. Our results indicate that an increased concentration of GHG leads to substantial increases in the extremes and their intensities. Hence, limiting CO2 emissions could substantially limit the risks associated with increases in extreme events in the twenty-first century.

scholarly journals A hydrological modelling-based approach for vulnerable area identification under changing climate scenarios

2020 ◽  
Author(s):  
Sonam S. Dash ◽  
Dipaka R. Sena ◽  
Uday Mandal ◽  
Anil Kumar ◽  
Gopal Kumar ◽  
...  
Keyword(s):  
Assessment Tool ◽  
Fold Increase ◽  
Maximum Temperature ◽  
Climate Scenarios ◽  
Vulnerable Area ◽  
Temperature And Precipitation ◽  
Monthly Streamflow ◽  
Rcp 8.5 ◽  
Streamflow Data ◽  
Critical Zones

Abstract The hydrologic behaviour of the Brahmani River basin (BRB) (39,633.90 km2), India was assessed for the base period (1970–1999) and future climate scenarios (2050) using the Soil and Water Assessment Tool (SWAT). Monthly streamflow data of 2000–2009 and 2010–2012 was used for calibration and validation, respectively, and performed satisfactorily with Nash-Sutcliffe Efficiency (ENS) of 0.52–0.55. The projected future climatic outcomes of the HadGEM2-ES model indicated that minimum temperature, maximum temperature, and precipitation may increase by 1.11–3.72 °C, 0.27–2.89 °C, and 16–263 mm, respectively, by 2050. The mean annual streamflow over the basin may increase by 20.86, 11.29, 4.45, and 37.94% under RCP 2.6, 4.5, 6.0, and 8.5, respectively, whereas the sediment yield is likely to increase by 23.34, 10.53, 2.45, and 27.62% under RCP 2.6, 4.5, 6.0, and 8.5, respectively, signifying RCP 8.5 to be the most adverse scenario for the BRB. Moreover, a ten-fold increase in environmental flow (defined as Q90) by the mid-century period is expected under the RCP 8.5 scenario. The vulnerable area assessment revealed that the increase in moderate and high erosion-prone regions will be more prevalent in the mid-century. The methodology developed herein could be successfully implemented for identification and prioritization of critical zones in worldwide river basins.

scholarly journals Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada

2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Negative Consequences ◽  
Temperature And Precipitation ◽  
Joint Occurrence

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

scholarly journals Climate Dynamics of the Spatiotemporal Changes of Vegetation NDVI in Northern China from 1982 to 2015

2021 ◽  
Vol 13 (2) ◽  
pp. 187
Author(s):  
Rui Sun ◽  
Shaohui Chen ◽  
Hongbo Su
Keyword(s):  
Solar Radiation ◽  
Vegetation Index ◽  
Global Climate ◽  
Regional Scale ◽  
Northern China ◽  
Climate Dynamics ◽  
High Coverage ◽  
Vegetation Growth ◽  
Temperature And Precipitation ◽  
Precipitation And Temperature

As an important part of a terrestrial ecosystem, vegetation plays an important role in the global carbon-water cycle and energy flow. Based on the Global Inventory Monitoring and Modeling System (GIMMS) third generation of Normalized Difference Vegetation Index (NDVI3g), meteorological station data, climate reanalysis data, and land cover data, this study analyzed the climate dynamics of the spatiotemporal variations of vegetation NDVI in northern China from 1982 to 2015. The results showed that growth season NDVI (NDVIgs) increased significantly at 0.006/10a (p < 0.01) in 1982–2015 on the regional scale. The period from 1982 to 2015 was divided into three periods: the NDVIgs increased by 0.026/10a (p < 0.01) in 1982–1990, decreased by −0.002/10a (p > 0.1) in 1990–2006, and then increased by 0.021/10a (p < 0.01) during 2006–2015. On the pixel scale, the increases in NDVIgs during 1982–2015, 1982–1990, 1990–2006, and 2006–2015 accounted for 74.64%, 85.34%, 48.14%, and 68.78% of the total area, respectively. In general, the dominant climate drivers of vegetation growth had gradually switched from solar radiation, temperature, and precipitation (1982–1990) to precipitation and temperature (1990–2015). For woodland, high coverage grassland, medium coverage grassland, low coverage grassland, the dominant climate drivers had changed from temperature and solar radiation, solar radiation and precipitation, precipitation and solar radiation, solar radiation to precipitation and solar radiation, precipitation, precipitation and temperature, temperature and precipitation. The areas controlled by precipitation increased significantly, mainly distributed in arid, sub-arid, and sub-humid areas. The dominant climate drivers for vegetation growth in the plateau climate zone or high-altitude area changed from solar radiation to temperature and precipitation, and then to temperature, while in cold temperate zone, changed from temperature to solar radiation. These results are helpful to understand the climate dynamics of vegetation growth, and have important guiding significance for vegetation protection and restoration in the context of global climate change.

scholarly journals Impact of Climate Change on Water Availability and Food Security of Nepal

2012 ◽  
pp. 59-63
Author(s):  
Roshan Kumar Mehta ◽  
Shree Chandra Shah
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Climatic Factors ◽  
Monsoon Season ◽  
Groundwater Table ◽  
Maximum Temperature ◽  
Aquatic Life ◽  
Temperature And Precipitation ◽  
Average Maximum ◽  
Water Scarce

The increase in the concentration of greenhouse gases (GHGs) in the atmosphere is widely believed to be causing climate change. It affects agriculture, forestry, human health, biodiversity, and snow cover and aquatic life. Changes in climatic factors like temperature, solar radiation and precipitation have potential to influence agrobiodiversity and its production. An average of 0.04°C/ year and 0.82 mm/year rise in annual average maximum temperature and precipitation respectively from 1975 to 2006 has been recorded in Nepal. Frequent droughts, rise in temperature, shortening of the monsoon season with high intensity rainfall, severe floods, landslides and mixed effects on agricultural biodiversity have been experienced in Nepal due to climatic changes. A survey done in the Chitwan District reveals that lowering of the groundwater table decreases production and that farmers are attracted to grow less water consuming crops during water scarce season. The groundwater table in the study area has lowered nearly one meter from that of 15 years ago as experienced by the farmers. Traditional varieties of rice have been replaced in the last 10 years by modern varieties, and by agricultural crops which demand more water for cultivation. The application of groundwater for irrigation has increased the cost of production and caused severe negative impacts on marginal crop production and agro-biodiversity. It is timely that suitable adaptive measures are identified in order to make Nepalese agriculture more resistant to the adverse impacts of climate change, especially those caused by erratic weather patterns such as the ones experienced recently.DOI: http://dx.doi.org/10.3126/hn.v11i1.7206 Hydro Nepal Special Issue: Conference Proceedings 2012 pp.59-63

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