scholarly journals Assessment of ECMWF SEAS5 Seasonal Forecast Performance over South America

2019 ◽  
Vol 35 (2) ◽  
pp. 561-584 ◽  
Author(s):  
S. Gubler ◽  
K. Sedlmeier ◽  
J. Bhend ◽  
G. Avalos ◽  
C. A. S. Coelho ◽  
...  
Keyword(s):  
South America ◽  
Minimum Temperature ◽  
High Performance ◽  
Austral Summer ◽  
Prediction Performance ◽  
Dynamical Model ◽  
Maximum Temperature ◽  
Forecast Performance ◽  
Empirical Prediction ◽  
The North

Abstract Seasonal predictions have a great socioeconomic potential if they are reliable and skillful. In this study, we assess the prediction performance of SEAS5, version 5 of the seasonal prediction system of the European Centre for Medium-Range Weather Forecasts (ECMWF), over South America against homogenized station data. For temperature, we find the highest prediction performances in the tropics during austral summer, where the probability that the predictions correctly discriminate different observed outcomes is 70%. In regions lying to the east of the Andes, the predictions of maximum and minimum temperature still exhibit considerable performance, while farther to the south in Chile and Argentina the temperature prediction performance is low. Generally, the prediction performance of minimum temperature is slightly lower than for maximum temperature. The prediction performance of precipitation is generally lower and spatially and temporally more variable than for temperature. The highest prediction performance is observed at the coast and over the highlands of Colombia and Ecuador, over the northeastern part of Brazil, and over an isolated region to the north of Uruguay during DJF. In general, Niño-3.4 has a strong influence on both air temperature and precipitation in the regions where ECMWF SEAS5 shows high performance, in some regions through teleconnections (e.g., to the north of Uruguay). However, we show that SEAS5 outperforms a simple empirical prediction based on Niño-3.4 in most regions where the prediction performance of the dynamical model is high, thereby supporting the potential benefit of using a dynamical model instead of statistical relationships for predictions at the seasonal scale.

scholarly journals Comparison of climatic variables among different climatic sub-regions of Bangladesh

2016 ◽  
Vol 29 (1) ◽  
pp. 63-71
Author(s):  
Md Younus Mia ◽  
Md Ramjan Ali ◽  
Shimul Roy
Keyword(s):  
Minimum Temperature ◽  
Moving Average ◽  
Maximum Temperature ◽  
Annual Average ◽  
Change Rate ◽  
The North ◽  
Eastern Zone ◽  
North Eastern ◽  
Western Zone ◽  
North Western

The study was conducted to compare the rate of change of selective climatic variables such as annual maximum and minimum temperature, annual total rainfall and annual average humidity among the three different climatic sub-regions (Western zone, northwestern zone and north-eastern zone) of Bangladesh. Annual averages of climatic parameters were calculated to analyze the trend lines, variation and change rate of climatic parameter during the study period. Five years moving average rainfall and humidity were also determined. It was observed that change rate of annual maximum temperature and annual average maximum temperature both were highest in north-eastern zone at the rate of 0.048 and 0.046°C per year, respectively. Highest annual minimum temperature change rate (0.003°C per year) was also found in the north-eastern zone but highest annual average minimum temperature change rate (0.034°C per year) was found in the north-western zone. Average annual rainfall was decreasing insignificantly in all the three climatic sub-regions whereas the highest change rate (21.50 mm per year) was observed in the north-eastern zone of Bangladesh. Highest annual average humidity change rate (0.113% per year) was found in the north-western zone of Bangladesh and five years moving average of annual average humidity was increasing at the highest rate of 0.132% per year in the north-western zone of Bangladesh.Bangladesh J. Sci. Res. 29(1): 63-71, June-2016

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.

Temperature Variability over South America

2009 ◽  
Vol 22 (22) ◽  
pp. 5854-5869 ◽  
Author(s):  
Jennifer M. Collins ◽  
Rosane Rodrigues Chaves ◽  
Valdo da Silva Marques
Keyword(s):  
South America ◽  
North Atlantic Ocean ◽  
Southern Oscillation ◽  
Austral Summer ◽  
Tropical Region ◽  
Supporting Evidence ◽  
Recent Period ◽  
Central Brazil ◽  
The North ◽  
Mean Temperature

Abstract The variation of air temperature at 2 m above the earth’s surface in South America (SA) between 1948 and 2007 is investigated primarily using the NCEP–NCAR reanalysis. In December–February (austral summer), the majority of SA has a mean temperature between 21° and 24°C during 1948–75, and for 1976–2007 the mean temperature is above 24°C. In June–August (austral winter), warmer temperatures are observed in the tropical region in the recent period. The results indicate that Northeast Brazil (NEB) and central Brazil are warmer in the more recent period. In the last seven years (2001–07) compared to the earlier periods, greater warming is noted in the tropical SA region, mainly in NEB and over the North Atlantic Ocean, and cooling is observed in part of the subtropical SA region. Supporting evidence for the warming in Brazil is given through analyses of station data and observational data. The results presented here indicate that the climate change over SA is likely not predominantly a result of variations in El Niño–Southern Oscillation (the most important coupled ocean–atmosphere phenomenon to produce climate variability over SA). Instead, the climate changes likely occur as a response to other natural variability of the climate and/or may be a result of human activity. However, even without ascertaining the specific causes, the most important finding in this work is to demonstrate that a change in the temperature patterns of SA occurred between 1948 and 2007.

scholarly journals Subseasonal prediction performance for austral summer South American rainfall

2020 ◽  
Author(s):  
Nicholas P. Klingaman ◽  
Matthew Young ◽  
Amulya Chevuturi ◽  
Bruno Guimaraes ◽  
Liang Guo ◽  
...  
Keyword(s):  
South America ◽  
Southern Oscillation ◽  
Austral Summer ◽  
Skill Score ◽  
Lead Times ◽  
South American ◽  
Forecast Performance ◽  
Conditional Performance ◽  
The Andes ◽  
Rainfall Variations

AbstractSkilful and reliable predictions of week-to-week rainfall variations in South America, two to three weeks ahead, are essential to protect lives, livelihoods and ecosystems. We evaluate forecast performance for weekly rainfall in extended austral summer (November–March) in four contemporary subseasonal systems, including a new Brazilian model, at 1–5 week leads for 1999–2010. We measure performance by the correlation coefficient (in time) between predicted and observed rainfall; we measure skill by the Brier Skill Score for rainfall terciles against a climatological reference forecast. We assess unconditional performance (i.e., regardless of initial condition) and conditional performance based on the initial phase of the Madden–Julian Oscillation (MJO) and the El Niño–Southern Oscillation (ENSO). All models display substantial mean rainfall biases, including dry biases in Amazonia and wet biases near the Andes, which are established by Week 1 and vary little thereafter. Unconditional performance extends to Week 2 in all regions except for Amazonia and the Andes, but to Week 3 only over northern, northeastern and southeastern South America. Skill for upper- and lower-tercile rainfall extends only to Week 1. Conditional performance is not systematically or significantly higher than unconditional performance; ENSO and MJO events provide limited “windows of opportunity” for improved S2S predictions that are region- and model-dependent. Conditional performance may be degraded by errors in predicted ENSO and MJO teleconnections to regional rainfall, even at short lead times.

A Synopsis of Dicliptera (Acanthaceae) in Brazil, with the Description of Two New Species

2020 ◽  
Vol 45 (2) ◽  
pp. 340-348
Author(s):  
James Lucas da Costa-Lima ◽  
Earl Celestino de Oliveira Chagas
Keyword(s):  
New Species ◽  
South America ◽  
The State ◽  
Northeastern Brazil ◽  
Mato Grosso ◽  
The North ◽  
New Synonyms ◽  
Two New Species ◽  
Mato Grosso Do Sul ◽  
A New Species

Abstract—A synopsis of Dicliptera (Acanthaceae) for Brazil is presented. Six species are recognized: Dicliptera ciliaris, D. sexangularis, and D. squarrosa, widely distributed in South America; D. purpurascens, which ranges from the North Region of Brazil (in the state of Acre) to eastern Bolivia; D. gracilirama, a new species from the Atlantic Forest of northeastern Brazil; and D. granchaquenha, a new species recorded in dry and semideciduous forests in Bolivia and western Brazil, in the state of Mato Grosso do Sul. Furthermore, we propose new synonyms and designate lectotypes for eleven names. An identification key to the six accepted Dicliptera species in Brazil is provided.

scholarly journals Spatiotemporal Evolution of Fractional Vegetation Cover and Its Response to Climate Change Based on MODIS Data in the Subtropical Region of China

2021 ◽  
Vol 13 (5) ◽  
pp. 913
Author(s):  
Hua Liu ◽  
Xuejian Li ◽  
Fangjie Mao ◽  
Meng Zhang ◽  
Di’en Zhu ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Distribution Area ◽  
Spatiotemporal Pattern ◽  
Climate Factors ◽  
Important Indicator ◽  
Fractional Vegetation Cover ◽  
Annual Minimum Temperature ◽  
Total Study Area

The subtropical vegetation plays an important role in maintaining the structure and function of global ecosystems, and its contribution to the global carbon balance are receiving increasing attention. The fractional vegetation cover (FVC) as an important indicator for monitoring environment change, is widely used to analyze the spatiotemporal pattern of regional and even global vegetation. China is an important distribution area of subtropical vegetation. Therefore, we first used the dimidiate pixel model to extract the subtropical FVC of China during 2001–2018 based on MODIS land surface reflectance data, and then used the linear regression analysis and the variation coefficient to explore its spatiotemporal variations characteristics. Finally, the partial correlation analysis and the partial derivative model were used to analyze the influences and contributions of climate factors on FVC, respectively. The results showed that (1) the subtropical FVC had obvious spatiotemporal heterogeneity; the FVC high-coverage and medium-coverage zones were concentratedly and their combined area accounted for more than 70% of the total study area. (2) The interannual variation in the average subtropical FVC from 2001 to 2018 showed a significant growth trend. (3) In 76.28% of the study area, the regional FVC showed an increasing trend, and the remaining regional FVC showed a decreasing trend. However, the overall fluctuations in the FVC (increasing or decreasing) in the region were relatively stable. (4) The influences of climate factors to the FVC exhibited obvious spatial differences. More than half of all pixels exhibited the influence of the average annual minimum temperature and the annual precipitation had positive on FVC, while the average annual maximum temperature had negative on FVC. (5) The contributions of climate changes to FVC had obvious heterogeneity, and the average annual minimum temperature was the main contribution factor affecting the dynamic variations of FVC.

scholarly journals Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Evergreen Forest ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Study Region ◽  
Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

scholarly journals The effect of average temperature on suicide rates in five urban California counties, 1999–⁠2019: an ecological time series analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sierra Cheng ◽  
Rebecca Plouffe ◽  
Stephanie M. Nanos ◽  
Mavra Qamar ◽  
David N. Fisman ◽  
...  
Keyword(s):  
Public Health ◽  
Suicide Rate ◽  
Minimum Temperature ◽  
The United States ◽  
Additive Models ◽  
Maximum Temperature ◽  
Mortality Data ◽  
Average Temperature ◽  
Suicide Rates ◽  
Average Maximum

Abstract Background Suicide is among the top 10 leading causes of premature morality in the United States and its rates continue to increase. Thus, its prevention has become a salient public health responsibility. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. The purpose of the present study is to evaluate the association between average temperature and suicide rates in the five most populous counties in California using mortality data from 1999 to 2019. Methods Monthly counts of death by suicide for the five counties of interest were obtained from CDC WONDER. Monthly average, maximum, and minimum temperature were obtained from nCLIMDIV for the same time period. We modelled the association of each temperature variable with suicide rate using negative binomial generalized additive models accounting for the county-specific annual trend and monthly seasonality. Results There were over 38,000 deaths by suicide in California’s five most populous counties between 1999 and 2019. An increase in average temperature of 1 °C corresponded to a 0.82% increase in suicide rate (IRR = 1.0082 per °C; 95% CI = 1.0025–1.0140). Estimated coefficients for maximum temperature (IRR = 1.0069 per °C; 95% CI = 1.0021–1.0117) and minimum temperature (IRR = 1.0088 per °C; 95% CI = 1.0023–1.0153) were similar. Conclusion This study adds to a growing body of evidence supporting a causal effect of elevated temperature on suicide. Further investigation into environmental causes of suicide, as well as the biological and societal contexts mediating these relationships, is critical for the development and implementation of new public health interventions to reduce the incidence of suicide, particularly in the face increasing temperatures due to climate change.

scholarly journals Effects of Cropland Expansion on Temperature Extremes in Western India from 1982 to 2015

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 489
Author(s):  
Jinxiu Liu ◽  
Weihao Shen ◽  
Yaqian He
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Land Cover ◽  
Minimum Temperature ◽  
Negative Impact ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Western India

India has experienced extensive land cover and land use change (LCLUC). However, there is still limited empirical research regarding the impact of LCLUC on climate extremes in India. Here, we applied statistical methods to assess how cropland expansion has influenced temperature extremes in India from 1982 to 2015 using a new land cover and land use dataset and ECMWF Reanalysis V5 (ERA5) climate data. Our results show that during the last 34 years, croplands in western India increased by ~33.7 percentage points. This cropland expansion shows a significantly negative impact on the maxima of daily maximum temperature (TXx), while its impacts on the maxima of daily minimum temperature and the minima of daily maximum and minimum temperature are limited. It is estimated that if cropland expansion had not taken place in western India over the 1982 to 2015 period, TXx would likely have increased by 0.74 (±0.64) °C. The negative impact of croplands on reducing the TXx extreme is likely due to evaporative cooling from intensified evapotranspiration associated with croplands, resulting in increased latent heat flux and decreased sensible heat flux. This study underscores the important influences of cropland expansion on temperature extremes and can be applicable to other geographic regions experiencing LCLUC.

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