scholarly journals Aridity Trends in Central America: A Spatial Correlation Analysis

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 427 ◽  
Author(s):  
Marcela Alfaro-Córdoba ◽  
Hugo G. Hidalgo ◽  
Eric J. Alfaro
Keyword(s):  
Monte Carlo ◽  
Central America ◽  
Spatial Correlation ◽  
Potential Evapotranspiration ◽  
Temporal Trends ◽  
Predictor Variable ◽  
Linear Regression Models ◽  
Infiltration Capacity ◽  
Monte Carlo Test ◽  
Near Surface

Trend analyses are common in several types of climate change studies. In many cases, finding evidence that the trends are different from zero in hydroclimate variables is of particular interest. However, when estimating the confidence interval of a set of hydroclimate stations or gridded data the spatial correlation between can affect the significance assessment using for example traditional non-parametric and parametric methods. For this reason, Monte Carlo simulations are needed in order to generate maps of corrected trend significance. In this article, we determined the significance of trends in aridity, modeled runoff using the Variable Infiltration Capacity Macroscale Hydrological model, Hagreaves potential evapotranspiration (PET) and near-surface temperature in Central America. Linear-regression models were fitted considering that the predictor variable is the time variable (years from 1970 to 1999) and predictand variable corresponds to each of the previously mentioned hydroclimate variables. In order to establish if the temporal trends were significantly different from zero, a Mann Kendall and a Monte Carlo test were used. The spatial correlation was calculated first to correct the variance of each trend. It was assumed in this case that the trends form a spatial stochastic process that can be modeled as such. Results show that the analysis considering the spatial correlation proposed here can be used for identifying those extreme trends. However, a set of variables with strong spatial correlation such as temperature can have robust and widespread significant trends assuming independence, but the vast majority of the stations can still fail the Monte Carlo test. We must be vigilant of the statistically robust changes in key primary parameters such as temperature and precipitation, which are the driving sources of hydrological alterations that may affect social and environmental systems in the future.

Crossover scaling in semidilute polymer solutions: a Monte Carlo test

1991 ◽  
Vol 1 (1) ◽  
pp. 37-60 ◽  
Author(s):  
Wolfgang Paul ◽  
Kurt Binder ◽  
Dieter W. Heermann ◽  
Kurt Kremer
Keyword(s):  
Monte Carlo ◽  
Polymer Solutions ◽  
Monte Carlo Test

scholarly journals Sensitivity of groundwater recharge using climatic analogues and HYDRUS-1D

2012 ◽  
Vol 16 (8) ◽  
pp. 2485-2497 ◽  
Author(s):  
B. Leterme ◽  
D. Mallants ◽  
D. Jacques
Keyword(s):  
Water Balance ◽  
Groundwater Recharge ◽  
Potential Evapotranspiration ◽  
Future Climate ◽  
Annual Precipitation ◽  
Balance Model ◽  
Subtropical Climate ◽  
Northern Spain ◽  
Near Surface ◽  
Hydrus 1D

Abstract. The sensitivity of groundwater recharge to different climate conditions was simulated using the approach of climatic analogue stations, i.e. stations presently experiencing climatic conditions corresponding to a possible future climate state. The study was conducted in the context of a safety assessment of a future near-surface disposal facility for low and intermediate level short-lived radioactive waste in Belgium; this includes estimation of groundwater recharge for the next millennia. Groundwater recharge was simulated using the Richards based soil water balance model HYDRUS-1D and meteorological time series from analogue stations. This study used four analogue stations for a warmer subtropical climate with changes of average annual precipitation and potential evapotranspiration from −42% to +5% and from +8% to +82%, respectively, compared to the present-day climate. Resulting water balance calculations yielded a change in groundwater recharge ranging from a decrease of 72% to an increase of 3% for the four different analogue stations. The Gijon analogue station (Northern Spain), considered as the most representative for the near future climate state in the study area, shows an increase of 3% of groundwater recharge for a 5% increase of annual precipitation. Calculations for a colder (tundra) climate showed a change in groundwater recharge ranging from a decrease of 97% to an increase of 32% for four different analogue stations, with an annual precipitation change from −69% to −14% compared to the present-day climate.

scholarly journals Spatial and temporal drivers of wildfire occurrence in the context of rural development in northern Wisconsin, USA

2012 ◽  
Vol 21 (2) ◽  
pp. 141 ◽  
Author(s):  
Brian R. Miranda ◽  
Brian R. Sturtevant ◽  
Susan I. Stewart ◽  
Roger B. Hammer
Keyword(s):  
Linear Regression ◽  
Land Use Planning ◽  
Temporal Trends ◽  
Point Pattern Analysis ◽  
Annual Number ◽  
Point Pattern ◽  
Linear Regression Models ◽  
Housing Density ◽  
Spatial And Temporal Scales ◽  
Wildfire Occurrence

Most drivers underlying wildfire are dynamic, but at different spatial and temporal scales. We quantified temporal and spatial trends in wildfire patterns over two spatial extents in northern Wisconsin to identify drivers and their change through time. We used spatial point pattern analysis to quantify the spatial pattern of wildfire occurrences, and linear regression to quantify the influence of drought and temporal trends in annual number and mean size of wildfires. Analyses confirmed drought as an important driver of both occurrences and fire size. When both drought and time were incorporated in linear regression models, the number of wildfires showed a declining trend across the full study area, despite housing density increasing in magnitude and spatial extent. Fires caused by campfires and debris-burning did not show any temporal trends. Comparison of spatial models representing biophysical, anthropogenic and combined factors demonstrated human influences on wildfire occurrences, especially human activity, infrastructure and property values. We also identified a non-linear relationship between housing density and wildfire occurrence. Large wildfire occurrence was predicted by similar variables to all occurrences, except the direction of influence changed. Understanding these spatial and temporal drivers of wildfire occurrence has implications for land-use planning, wildfire suppression strategies and ecological goals.

scholarly journals Evaluation of three new surface irrigation parameterizations in the WRF-ARW v3.8.1 model: the Po Valley (Italy) case study

2020 ◽  
Vol 13 (7) ◽  
pp. 3179-3201
Author(s):  
Arianna Valmassoi ◽  
Jimy Dudhia ◽  
Silvana Di Sabatino ◽  
Francesco Pilla
Keyword(s):  
Potential Evapotranspiration ◽  
Mediterranean Area ◽  
Maximum Temperature ◽  
Surface Irrigation ◽  
Start Time ◽  
Near Surface ◽  
Local Climate ◽  
Po Valley ◽  
Soil Variables ◽  
Water Amount

Abstract. Irrigation is a method of land management that can affect the local climate. Recent literature shows that it affects mostly the near-surface variables and it is associated with an irrigation cooling effect. However, there is no common parameterization that also accounts for a realistic water amount, and this factor could ascribe one cause to the different impacts found in previous studies. This work aims to introduce three new surface irrigation parameterizations within the WRF-ARW model (v3.8.1) that consider different evaporative processes. The parameterizations are tested on one of the regions where global studies disagree on the signal of irrigation: the Mediterranean area and in particular the Po Valley. Three sets of experiments are performed using the same irrigation water amount of 5.7 mm d−1, derived from Eurostat data. Two complementary validations are performed for July 2015: monthly mean, minimum, and maximum temperature with ground stations and potential evapotranspiration with the MODIS product. All tests show that for both mean and maximum temperature, as well as potential evapotranspiration simulated fields approximate observation-based values better when using the irrigation parameterizations. This study addresses the sensitivity of the results to human-decision assumptions of the parameterizations: start time, length, and frequency. The main impact of irrigation on surface variables such as soil moisture is due to the parameterization choice itself affecting evaporation, rather than the timing. Moreover, on average, the atmosphere and soil variables are not very sensitive to the parameterization assumptions for realistic timing and length.

scholarly journals Impact of land–water sensitivity contrast on MOPITT retrievals and trends over a coastal city

2020 ◽  
Vol 13 (7) ◽  
pp. 3521-3542
Author(s):  
Ian Ashpole ◽  
Aldona Wiacek
Keyword(s):  
Transport Model ◽  
Weighted Least Squares ◽  
Temporal Trends ◽  
Lower Troposphere ◽  
Near Surface ◽  
Surface Level ◽  
Coastal City ◽  
Water Sensitivity ◽  
Land Water ◽  
Co Concentrations

Abstract. We compare MOPITT Version 7 (V7) Level 2 (L2) and Level 3 (L3) carbon monoxide (CO) products for the 1∘×1∘ L3 grid box containing the coastal city of Halifax, Canada (longitude −63.58∘, latitude 44.65∘), with a focus on the seasons DJF and JJA, and highlight a limitation in the L3 products that has significant consequences for the temporal trends in near-surface CO identified using those data. Because this grid box straddles the coastline, the MOPITT L3 products are created from the finer spatial resolution L2 products that are retrieved over both land and water, with a greater contribution from retrievals over water because more of the grid box lies over water than land. We create alternative L3 products for this grid box by separately averaging the bounded L2 retrievals over land (L3L) and water (L3W) and demonstrate that profile and total column CO (TCO) concentrations, retrieved at the same time, differ depending on whether the retrieval took place over land or water. These differences (ΔRET) are greatest in the lower troposphere (LT), where mean retrieved volume mixing ratios (VMRs) are greater in L3W than L3L, with maximum mean differences of 11.6 % (14.3 ppbv, p=0.001) at the surface level in JJA. Retrieved CO concentrations are more similar, on average, in the middle and upper troposphere (MT and UT), although large differences (in excess of 40 %) do infrequently occur. TCO is also greater in L3W than L3L in both seasons. By analysing L3L and L3W retrieval averaging kernels and simulations of these retrievals, we demonstrate that, in JJA, ΔRET is strongly influenced by differences in retrieval sensitivity over land and water, especially close to the surface where L3L has significantly greater information content than L3W. In DJF, land–water differences in retrieval sensitivity are much less pronounced and appear to have less of an impact on ΔRET, which analysis of wind directions suggests is more likely to reflect differences in true profile concentrations (i.e. real differences). The original L3 time series for the 1∘×1∘ grid box containing Halifax (L3O) corresponds much more closely to L3W than L3L, owing to the greater contribution from L2 retrievals over water than land. Thus, in JJA, variability in retrieved CO concentrations close to the surface in L3O is suppressed compared to L3L, and a declining trend detected using weighted least squares (WLS) regression analysis is significantly slower in L3O (strongest surface level trend identifiable is −1.35 (±0.35) ppbv yr−1) than L3L (−2.85 (±0.60) ppbv yr−1). This is because contributing L2 retrievals over water are closely tied to a priori CO concentrations used in the retrieval, owing to their lack of near-surface sensitivity in JJA, and these are based on monthly climatological CO profiles from a chemical transport model and therefore have no yearly change (surface level trend in L3W is −0.60 (±0.33) ppbv yr−1). Although our analysis focuses on DJF and JJA, we demonstrate that the findings also apply to MAM and SON. The results that we report here suggest that similar analyses be performed for other coastal cities before using MOPITT surface CO.

Abstract TMP65: Depth of Hospital Participation in Telestroke is Associated with Faster Door-to-Needle Time for Stroke Patients

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Arianna Moreno ◽  
Khawja A Saddiqui ◽  
Anand Viswanathan ◽  
Cynthia Whitney ◽  
Natalia Rost ◽  
...  
Keyword(s):  
Temporal Trends ◽  
Predictor Variable ◽  
Median Number ◽  
Hospital Level ◽  
Time Data ◽  
Frequent Contact ◽  
Frequent Use ◽  
The Relationship ◽  
Median Hospital ◽  
Primary Predictor

Background: Telestroke increases tPA use at spoke hospitals, yet its effect on door-to-needle (DTN) times is unknown. More frequent use of telestroke may introduce delays in DTN time or may improve it as practice leads to streamlined processes. Hypothesis: We hypothesize that spoke hospitals with more frequent contact to a hub hospital will have shorter DTN times than those with less frequent contact. Methods: We identified 367 patients treated with tPA by conventional or telestroke methods in the MGH Telestroke network for whom date and time data were available. Strength of the spoke-MGH connection was the primary predictor variable, defined as the number of all telestroke consults (tPA and non-tPA) done at each spoke hospital during the year of the patient’s presentation. Patient-level regression analyses examined the relationship between DTN time and spoke-MGH connection. We controlled for hospitals’ tPA volume, temporal trends, and clustering within hospitals. Results: Sixteen spoke hospitals contributed data on 367 tPA-treated patients from 2006-2016. Hospitals treated a median of 12.5 patients with tPA (IQR 7-33.5). Median hospital-level DTN was 78.8 minutes (IQR 71.3-85). Median number of telestroke consults per year was 37 (IQR 15-60). Among all 367 patients, median DTN was 76 minutes (IQR 61-98), and 24.8% of patients were treated within 60 minutes (n=91). Strength of connection between the spoke and hub hospital was significantly associated with faster DTN time for patients (1.8 minute gain per 10 additional consults, p<0.001) and increased likelihood of tPA delivery within 60 minutes (OR 1.01, p<0.001). Conclusion: More frequent contact between a telestroke spoke and its hub was associated with faster tPA delivery for patients, even after accounting for hospitals’ tPA volume and secular trends in DTN improvements. This highlights added benefits of increased utilization of telestroke.

scholarly journals Quantifying the effect of seasonal and vertical habitat tracking on planktonic foraminifera proxies

2017 ◽  
Vol 13 (6) ◽  
pp. 573-586 ◽  
Author(s):  
Lukas Jonkers ◽  
Michal Kučera
Keyword(s):  
Environmental Change ◽  
Data Model ◽  
Model Comparison ◽  
Planktonic Foraminifera ◽  
Temporal Trends ◽  
Global Scale ◽  
Individual Species ◽  
Near Surface ◽  
Proxy Records ◽  
Habitat Tracking

Abstract. The composition of planktonic foraminiferal (PF) calcite is routinely used to reconstruct climate variability. However, PF ecology leaves a large imprint on the proxy signal: seasonal and vertical habitats of PF species vary spatially, causing variable offsets from annual mean surface conditions recorded by sedimentary assemblages. PF seasonality changes with temperature in a way that minimises the environmental change that individual species experience and it is not unlikely that changes in depth habitat also result from such habitat tracking. While this behaviour could lead to an underestimation of spatial or temporal trends as well as of variability in proxy records, most palaeoceanographic studies are (implicitly) based on the assumption of a constant habitat. Up to now, the effect of habitat tracking on foraminifera proxy records has not yet been formally quantified on a global scale. Here we attempt to characterise this effect on the amplitude of environmental change recorded in sedimentary PF using core top δ18O data from six species. We find that the offset from mean annual near-surface δ18O values varies with temperature, with PF δ18O indicating warmer than mean conditions in colder waters (on average by −0.1 ‰ (equivalent to 0.4 °C) per °C), thus providing a first-order quantification of the degree of underestimation due to habitat tracking. We use an empirical model to estimate the contribution of seasonality to the observed difference between PF and annual mean δ18O and use the residual Δδ18O to assess trends in calcification depth. Our analysis indicates that given an observation-based model parametrisation calcification depth increases with temperature in all species and sensitivity analysis suggests that a temperature-related seasonal habitat adjustment is essential to explain the observed isotope signal. Habitat tracking can thus lead to a significant reduction in the amplitude of recorded environmental change. However, we show that this behaviour is predictable. This allows accounting for habitat tracking, enabling more meaningful reconstructions and improved data–model comparison.

Sign in / Sign up

Export Citation Format

Share Document