scholarly journals Temperatura e precipitação: futuros cenários do município de Taubaté, SP, Brasil

2016 ◽  
Vol 11 (5) ◽  
pp. 1068
Author(s):  
Thiago Adriano dos Santos ◽  
Gilberto Fisch
Keyword(s):  
Climate Model ◽  
Model Simulation ◽  
Summer Rainfall ◽  
Seasonal Distribution ◽  
Future Time ◽  
Time Intervals ◽  
Average Temperature ◽  
Monthly Average ◽  
Temperature And Precipitation ◽  
Accumulated Rainfall

This work quantified temperature and precipitation variations in the region of Taubate using historic precipitation data and temperature simulations (climatology from 1961 to 1990). Corrections were made based on the observational data, and simulations of future time intervals (2011-2040, 2041-2070, 2071-2099) using a climate-model simulation. Thus, it is possible to predict an increase of 3.6°C in the average annual air temperature and an increase of 231 mm in annual accumulated rainfall (equivalent to approximately 17% of the climatological normal) for the interval 2071-2099. Moreover, in relation to seasonal distribution, there is a higher monthly average temperature increase in the spring (4.1°C) and lower in the summer (3.4°C) and a higher average daily increase in summer rainfall (1.1 mm) and smaller increase in spring (0.3 mm). There is also an increase of approximately 5 days in the daily number of days with greater than 1mm precipitation throughout the year. The analysis of the water balance showed deficits in the months of August and September and found a disparity between the input and output of water entering the territory through precipitation, evapotranspiration, and water consumption, suggesting the need to adapt to new social and environmental scenarios.

scholarly journals The Temperature of Japan Modelling Japan’s Average Monthly Temperature from 1901 to 2015

2018 ◽  
Vol 2 (3) ◽  
pp. 224-228
Author(s):  
Batol Shiwa Hashimi ◽  
Aissa Boudjella ◽  
Wagma Saboor
Keyword(s):  
Time Series ◽  
Polynomial Regression ◽  
Polynomial Function ◽  
Average Difference ◽  
Time Intervals ◽  
Average Temperature ◽  
Monthly Average ◽  
The Past ◽  
Temperature Trends ◽  
The Relationship

The purpose of this investigation is to examine the variation of temperature in Japan over the past 114 years. The historical dataset of the monthly average temperature from 1901 to 2015 were analyzed. The relationship between temperature and time during the four time intervals, i.e (1901 -1930), (1931-1960), (1961-1990) and (1991-2015) is described using a new analytical model based on the last –square method of estimation. We accurately fit a polynomial regression trend of degree 4 to the time series to describe the temperature variation. The results show the average difference of temperature between 2015 and 1901 increases about 0.97 °C. The average monthly difference between the maximum and minimum temperature was approximately 2.11 °C. This approach of modeling temperature using regression form significantly simplifies the data analysis. The information from data, namely the variation of the temperature, maybe be obtained from the extracted parameters such as slope, y-intercept, and the coefficients of polynomial function that are a function of time. More importantly, the parameters that describe the time variation temperature trends over 115 years obtained with a high R-squared do not vary significantly. This is in agreement with the Earth’s average temperature that has climbed to more 1 oC.

scholarly journals Greenland temperature and precipitation over the last 20,000 years using data assimilation

2020 ◽  
Author(s):  
Jessica A. Badgeley ◽  
Eric J. Steig ◽  
Gregory J. Hakim ◽  
Tyler J. Fudge
Keyword(s):  
Data Assimilation ◽  
Spatial Patterns ◽  
Climate Model ◽  
Model Simulation ◽  
Ice Core ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Temperature And Precipitation ◽  
Paleoclimate Data ◽  
Ice Core Records

Abstract. Reconstructions of past temperature and precipitation are fundamental to modeling the Greenland Ice Sheet and assessing its sensitivity to climate. Paleoclimate information is sourced from proxy records and climate-model simulations; however, the former are spatially incomplete while the latter are sensitive to model dynamics and boundary conditions. Efforts to combine these sources of information to reconstruct spatial patterns of Greenland climate over glacial-interglacial cycles have been limited by assumptions of fixed spatial patterns and a restricted use of proxy data. We avoid these limitations by using paleoclimate data assimilation to create independent reconstructions of temperature and precipitation for the last 20,000 years. Our method uses information from long ice-core records and extends it to all locations across Greenland using spatial relationships derived from a transient climate-model simulation. Our reconstructions evaluate well against independent ice-core records. In addition, we find that the relationship between precipitation and temperature is frequency dependent and spatially variable, suggesting that thermodynamic scaling methods commonly used in ice-sheet modeling are overly simplistic. Our results demonstrate that paleoclimate data assimilation is a useful tool for reconstructing the spatial and temporal patterns of past climate on timescales relevant to ice sheets.

scholarly journals Regional climate model data used within the SWURVE project – 2: addressing uncertainty in regional climate model data for five European case study areas

2007 ◽  
Vol 11 (3) ◽  
pp. 1085-1096 ◽  
Author(s):  
M. Ekström ◽  
B. Hingray ◽  
A. Mezghani ◽  
P. D. Jones
Keyword(s):  
Probability Distribution ◽  
Climate Model ◽  
Regional Climate ◽  
Model Data ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Regional Temperature ◽  
Scaling Variables ◽  
Annual Average Temperature

Abstract. To aid assessments of the impact of climate change on water related activities in the case study regions (CSRs) of the EC-funded project SWURVE, estimates of uncertainty in climate model data need to be developed. This paper compares two methods for estimating uncertainty in annual surface temperature and precipitation for the period 2070–2099. Both combine probability distribution functions for global temperature increase and for scaling variables (i.e. the change in regional temperature/precipitation per degree of global annual average temperature change) to produce a probability distribution for regional temperature and precipitation. The methods differ in terms of the distribution used for the respective probability distribution function. For scaling variables, the first method assumes a uniform distribution, whilst the second method assumes a normal distribution. For the probability distribution function of global annual average temperature change, the first method uses a uniform distribution and the second uses a log-normal approximation to a distribution derived from Wigley and Raper, 2001. Although the methods give somewhat different ranges of change, they agree on how temperature and precipitation in each of the CSRs are likely to change relative to each other. For annual surface temperature, both methods predict increases in all CSRs, although somewhat less so for NW England (5th and 95th percentiles vary between 1.1–1.9°C to 3.8–5.7°C) and about 1.7–3.1°C to 5.3–8.6°C for the others. For precipitation, most probability distributions (except for NW England) show predominantly decreasing precipitation, particularly so for the Iberian CSR (5th and 95th percentiles vary from –29.3 to –44% to –9.6 to –4%).

scholarly journals Projected Changes in Extreme Temperature and Precipitation Indices Over CORDEX-MENA Domain

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 622
Author(s):  
Tugba Ozturk ◽  
F. Sibel Saygili-Araci ◽  
M. Levent Kurnaz
Keyword(s):  
Regional Climate Model ◽  
Radiative Forcing ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Extreme ◽  
Pronounced Increase ◽  
Temperature And Precipitation ◽  
Projected Changes ◽  
Extreme Indices

In this study, projected changes in climate extreme indices defined by the Expert Team on Climate Change Detection and Indices were investigated over Middle East and North Africa. Changes in the daily maximum and minimum temperature- and precipitation- based extreme indices were analyzed for the end of the 21st century compared to the reference period 1971–2000 using regional climate model simulations. Regional climate model, RegCM4.4 was used to downscale two different global climate model outputs to 50 km resolution under RCP4.5 and RCP8.5 scenarios. Results generally indicate an intensification of temperature- and precipitation- based extreme indices with increasing radiative forcing. In particular, an increase in annual minimum of daily minimum temperatures is more pronounced over the northern part of Mediterranean Basin and tropics. High increase in warm nights and warm spell duration all over the region with a pronounced increase in tropics are projected for the period of 2071–2100 together with decrease or no change in cold extremes. According to the results, a decrease in total wet-day precipitation and increase in dry spells are expected for the end of the century.

Future Extreme Climates Projection over Huang-Huai-Hai Region of China

2014 ◽  
Vol 955-959 ◽  
pp. 3887-3892 ◽  
Author(s):  
Huang He Gu ◽  
Zhong Bo Yu ◽  
Ji Gan Wang
Keyword(s):  
Climate Changes ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
Huai River ◽  
The Future

This study projects the future extreme climate changes over Huang-Huai-Hai (3H) region in China using a regional climate model (RegCM4). The RegCM4 performs well in “current” climate (1970-1999) simulations by compared with the available surface station data, focusing on near-surface air temperature and precipitation. Future climate changes are evaluated based on experiments driven by European-Hamburg general climate model (ECHAM5) in A1B future scenario (2070-2099). The results show that the annual temperature increase about 3.4 °C-4.2 °C and the annual precipitation increase about 5-15% in most of 3H region at the end of 21st century. The model predicts a generally less frost days, longer growing season, more hot days, no obvious change in heat wave duration index, larger maximum five-day rainfall, more heavy rain days, and larger daily rainfall intensity. The results indicate a higher risk of floods in the future warmer climate. In addition, the consecutive dry days in Huai River Basin will increase, indicating more serve drought and floods conditions in this region.

Sign in / Sign up

Export Citation Format

Share Document