Changes in Temperature-based Extremes Indices Due to Global Warming Projected by a Global 20-km-mesh Atmospheric Model

Uchiyama, Takao; Mizuta, Ryo; Kamiguchi, Kenji; Noda, Akira

doi:10.2151/sola.2006-018

Cited by 16 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A gradual increase in temperature with time is also evident. This result is consistent with IPCC findings (McCarthy et al, 2001) as well as the recent results of Uchiyama et al (2006), who found that mean temperature has increased worldwide. Hence, PRECIS can detect the rise in temperature in Bangladesh well, which may be considered as a signature of global warming having significant implications for monsoon-influenced regions (Chase et al, 2003).…”

Section: Annual and Decadal Temperaturesupporting

confidence: 93%

See 1 more Smart Citation

Calibration of PRECIS in employing future scenarios in Bangladesh

Islam

Rafiuddin

Ahmed

et al. 2007

Intl Journal of Climatology

View full text Add to dashboard Cite

Providing Regional Climates for Impacts Studies (PRECIS) is a regional climate model, which is used for the simulation of regional-scale climatology at high resolution (i.e. 50-km horizontal resolution). The calibration of rainfall and temperature simulated by PRECIS is performed in Bangladesh with the surface observational data from the Bangladesh Meteorological Department (BMD) for the period . The Climate Research Unit (CRU) data is also used for understanding the performance of the model. The results for the period 1961-1990 are used as a reference to find the variation of PRECIS-projected rainfall and temperature in 2071, in and around Bangladesh, as an example. Analyses are performed using the following two methods: (1) grid-to-grid and (2) point-to-point analyses. It is found that grid-to-grid analysis provides overestimation of PRECIS in Bangladesh because of downscaling of observed data when gridded from asymmetric low-density data network of BMD. On the other hand, model data extracted at observational sites provide better performance of PRECIS. The model overestimates rainfall in dry and pre-monsoon periods, whereas it underestimates it in the monsoon period. Overall, PRECIS is found to be able to estimate about 92% of surface rainfall. Model performance in estimating rainfall increases substantially with the increase in the length of time series of datasets. Systematic cold bias is found in simulating the annual scale of the surface temperature. In the annual scale, the model underestimates temperature of about 0.61°C that varies within a range of +1.45°C to −3.89°C in different months. This analysis reveals that rainfall and temperature will be increased in Bangladesh in 2071. On the basis of the analyses, look-up tables for rainfall and temperature were prepared in a bid to calibrate PRECIS simulation results for Bangladesh. The look-up tables proposed in this analysis can be employed in the application of the projected rainfall and temperature in different sectors of the country. These look-up tables are useful only for the calibration of PRECIS simulation results for future climate projection for Bangladesh.

show abstract

Section: Annual and Decadal Temperaturesupporting

confidence: 93%

“…The variation in temperature (i.e. cold bias in the dry season and hot bias in the rainy season) may be due to the decrease and increase of latent heat flux for the two seasons respectively, (Uchiyama et al, 2006) which may not be well distinguished by the model.…”

Section: Calibration Of Temperaturementioning

confidence: 99%

Calibration of PRECIS in employing future scenarios in Bangladesh

Islam

Rafiuddin

Ahmed

et al. 2007

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…Table 3, which relates the predicted changes in annual mean climatic conditions to the current geographic variation across five sample locations, offers some guidance on agricultural adaptability. The table reports the baseline (1981-1990) annual mean temperature and precipitation (baseline climate data) and the conditions in 2091-2100 as estimated in the high-resolution atmospheric general circulation model (33,34) used by the World Bank, among others. Columbus, OH, serves as useful point of comparison, because its 1981-1990 conditions closely approximated the annual mean climatic conditions that existed near the geographic center of the distribution of North American wheat production in 1839 (35).…”

Section: Resultsmentioning

confidence: 99%

Adapting North American wheat production to climatic challenges, 1839–2009

Olmstead

Rhode

2010

Proc. Natl. Acad. Sci. U.S.A.

144

View full text Add to dashboard Cite

The Intergovernmental Panel on Climate Change projects that temperatures in the major grain-growing areas of North America will rise by 3–4 °C by 2100. Such abrupt changes will create major challenges, significantly altering the area suitable for wheat. The historical record offers insight into the capability of agriculture to adapt to climatic challenges. Using a new county-level dataset on wheat production and climate norms, we show that during the 19th and 20th centuries North American grain farmers pushed wheat production into environments once considered too arid, too variable, and too harsh to cultivate. As summary measures, the median annual precipitation norm of the 2007 distribution of North American wheat production was one-half that of the 1839 distribution, and the median annual temperature norm was 3.7 °C lower. This shift, which occurred mostly before 1929, required new biological technologies. The Green Revolution associated with the pioneering work of Norman Borlaug represented an important advance in this longer process of biological innovation. However, well before the Green Revolution, generations of North American farmers overcame significant climatic challenges.

show abstract

“…However for pre-monsoon and monsoon summer months (March-September), the deviation is much less, 4.67% and 0.79%, respectively. Such a variation in temperature (i.e., cold bias in the dry season and hot bias in the rainy season) may be due to the decrease and increase of latent heat flux for the two seasons, respectively [26], which may not be well distinguished by the model. …”

Section: Model Validationmentioning

confidence: 99%

A Comprehensive Modeling Study on Regional Climate Model (RCM) Application — Regional Warming Projections in Monthly Resolutions under IPCC A1B Scenario

Rajib

Rahman

2012

Atmosphere

View full text Add to dashboard Cite

Some of the major dimensions of climate change include increase in surface temperature, longer spells of droughts in significant portions of the world, associated higher evapotranspiration rates, and so on. It is therefore essential to comprehend the future possible scenario of climate change in terms of global warming. A high resolution limited area Regional Climate Model (RCM) can produce reasonably appropriate projections to be used for climate-scenario generation in country-scale. This paper features the development of future surface temperature projections for Bangladesh on monthly resolution for each year from 2011 to 2100 applying Providing Regional Climates for Impacts Studies (PRECIS), and it explains in detail the modeling processes including the model features, domain size selection, bias identification as well as construction of change field for the concerned climatic variable, in this case, surface temperature. PRECIS was run on a 50 km horizontal grid-spacing under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario and it was found to perform reasonably well in simulating future surface temperature of Bangladesh Apart from these quantitative analyses of temporal changes of temperature, this paper also illustrates their spatial distribution with a view to identify the most vulnerable zones under consequent warming through future times.

show abstract

Changes in Temperature-based Extremes Indices Due to Global Warming Projected by a Global 20-km-mesh Atmospheric Model

Cited by 16 publications

References 15 publications

Calibration of PRECIS in employing future scenarios in Bangladesh

Calibration of PRECIS in employing future scenarios in Bangladesh

Adapting North American wheat production to climatic challenges, 1839–2009

A Comprehensive Modeling Study on Regional Climate Model (RCM) Application — Regional Warming Projections in Monthly Resolutions under IPCC A1B Scenario

Contact Info

Product

Resources

About