scholarly journals STOCHASTIC TYPHOON MODEL AND ITS APPLICATION TO FUTURE TYPHOON PROJECTION

2011 ◽  
Vol 1 (32) ◽  
pp. 16 ◽  
Author(s):  
Tomohiro Yasuda ◽  
Hajime Mase ◽  
Shoji Kunitomi ◽  
Nobuhito Mori ◽  
Yuta Hayashi

This study presents a stochastic typhoon model (STM) for estimating the characteristics of typhoons in the present and future climate conditions. Differences of statistical characteristics between present and future typhoons were estimated from projections by an Atmospheric General Circulation Model (AGCM) under a climate change scenario and are taken into account in the stochastic modelling of future typhoons as a climate change signal. From the STM results which utilize the Monte Carlo simulation, it was found that the frequency of typhoon landfall in Osaka bay area, Japan, will decrease, although the mean value of atmospheric central pressure of typhoon will not change significantly. The arrival probability of stronger typhoons will increase in the future climate scenario.

2020 ◽  
Author(s):  
TERESSA NEGASSA MULETA

Abstract BackgroundRelatively few studies have addressed water management and adaptation measures in the face of changing water balances due to climate change. Projection of the future climate variables is done using General Circulation Model (GCM). But GCM cannot capture finer scale forcing variables at regional and basin levels. Hence Regional Climate Model (RCM) downscaled data for A1B emission scenario is bias corrected at basin level using observed data. The current study has developed future climate trends using the bias corrected RCM output data for Baro-Akobo River Basin with the basic objective of producing informative data for sustainable water resource development and management in the basin. ResultThe projected future climate shows an increasing trend for both maximum and minimum temperatures; however, for the case of precipitation it doesn’t manifest a systematic increasing or decreasing trend in the next century. The projected mean annual temperature increases from the baseline period by an amount of 1oC and 3.5oC respectively, in 2040s and 2090s. Similarly, evapotranspiration has been found to increase to an extent of 25% over the basin. The precipitation experiences a mean annual decrease by 1.8% in 2040s and increases by 1.8% in 2090s over the basin for the A1B emission scenario. ConclusionIrrespective of whether there is a trend or not, it can be concluded from these results that considerable change in climate is expected to happen over the basin as per the A1B emission scenario. In addition to quantitative change, the results of this study have depicted a considerable climate change in terms of timing and frequency and hence calls for an attention on the possible future risks of sustainable water resources development and management in the basin.


2012 ◽  
Vol 12 (12) ◽  
pp. 5367-5390 ◽  
Author(s):  
J. Kelly ◽  
P. A. Makar ◽  
D. A. Plummer

Abstract. Ten year simulations of North American current and future air-quality were carried out using a regional air-quality model driven by a regional climate model, in turn driven by a general circulation model. Three separate summer scenarios were performed: a scenario representing the years 1997 to 2006, and two SRES A2 climate scenarios for the years 2041 to 2050. The first future climate scenario makes use of 2002 anthropogenic precursor emissions, and the second applied emissions scaling factors derived from the IPCC Representative Concentration Pathway 6 (RCP 6) scenario to estimate emissions for 2050 from existing 2020 projections. Ten-year averages of ozone and PM2.5 at North American monitoring network stations were used to evaluate the model's current chemical climatology. The model was found to have a similar performance for ozone as when driven by an operational weather forecast model. The PM2.5 predictions had larger negative biases, likely resulting from the absence of rainwater evaporation, and from sub-regional negative biases in the surface temperature fields, in the version of the climate model used here. The differences between the two future climate simulations and the current climate simulation were used to predict the changes to air-quality that might be expected in a future warmer climate, if anthropogenic precursor emissions remain constant at their current levels, versus if the RCP 6 emissions controls were adopted. Metrics of concentration, human health, and ecosystem damage were compared for the simulations. The scenario with future climate and current anthropogenic emissions resulted in worse air-quality than for current conditions – that is, the effect of climate-change alone, all other factors being similar, would be a worsening of air-quality. These effects are spatially inhomogeneous, with the magnitude and sign of the changes varying with region. The scenario with future climate and RCP 6 emissions for 2050 resulted in an improved air-quality, with decreases in key pollutant concentrations, in acute human mortality associated with air-pollution, and in sulphur and ozone deposition to the ecosystem. The positive outcomes of the RCP 6 emissions reductions were found to be of greater magnitude than the negative outcomes of climate change alone. The RCP 6 scenario however resulted in an increase in the deposition of nitrogen, as a result of increased ammonia emissions expected in that scenario, compared to current ammonia emissions levels. The results of the study raise the possibility that simultaneous reductions of greenhouse gases and air pollution precursors may further reduce air pollution levels, with the added benefits of an immediate reduction in the impacts of air pollution on human and ecosystem health. Further scenarios to investigate this possibility are therefore recommended.


2010 ◽  
Vol 40 (8) ◽  
pp. 1576-1587 ◽  
Author(s):  
Ashley M. Thomson ◽  
Kevin A. Crowe ◽  
William H. Parker

Optimal breeding zones were developed for white spruce ( Picea glauca (Moench) Voss) in Ontario under present and future climate conditions to examine potential shifts due to climate change. These zones were developed by (i) determining a set of candidate breeding zones based on the relationship between measured performance variables and climate and (ii) employing a decision support model to select subsets of breeding zones that maximize geographic coverage subject to a constraint on the maximum number of zones. Current optimal breeding zones were based on 1961–1990 climate normals, and future breeding zones were based on three general circulation model (CGCM2, HADCM3, and CSIRO) predictions of 2041–2070 climate. Based on a maximum adaptive distance of 2.0 least significant difference values between sites within zones, 14 zones were required to cover the Ontario range of white spruce for the 1961–1990 data. Compared with breeding zones of other boreal conifers, current optimal breeding zones for white spruce were quite large, spanning up to 3° latitude and 10°–12° longitude and indicating large distances of effective seed transfer. Of the three general circulation models used to simulate future climate, HADCM3 B2 and CGCM2 B2 predicted 2041–2070 breeding zones that largely coincide with 1961–1990 zones. In contrast, CSIRO B2 indicated much narrower 2041–2070 breeding zones.


Author(s):  
Subhankar Debnath ◽  
Ashok Mishra ◽  
D. R. Mailapalli ◽  
N. S. Raghuwanshi ◽  
V. Sridhar

Abstract Climate change evokes future food security concerns and needs for sustainable intensification of agriculture. The explicit knowledge about crop yield gap at country level may help in identifying management strategies for sustainable agricultural production to meet future food demand. In this study, we assessed the rice yield gap under projected climate change scenario in India at 0.25° × 0.25° spatial resolution by using the Decision Support System for Agrotechnology Transfer (DSSAT) model. The simulated spatial yield results show that mean actual yield under rainfed conditions (Ya) will reduce from 2.13 t/ha in historical period 1981–2005 to 1.67 t/ha during the 2030s (2016–2040) and 2040s (2026–2050), respectively, under the RCP 8.5 scenario. On the other hand, mean rainfed yield gap shows no change (≈1.49 t/ha) in the future. Temporal analysis of yield indicates that Ya is expected to decrease in the considerably large portion of the study area (30–60%) under expected future climate conditions. As a result, yield gap is expected to either stagnate or increase in 50.6 and 48.7% of the study area during the two future periods, respectively. The research outcome indicates the need for identifying plausible best management strategies to reduce the yield gap under expected future climate conditions for sustainable rice production in India.


MAUSAM ◽  
2021 ◽  
Vol 52 (1) ◽  
pp. 229-244
Author(s):  
K. RUPA KUMAR ◽  
R. G. ASHRIT

The regional climatic impacts associated with global climatic change and their assessment are very important since agriculture, water resources, ecology etc., are all vulnerable to climatic changes on regional scale. Coupled Atmosphere-Ocean general circulation model (AOGCM) simulations provide a range of scenarios, which can be used, for the assessment of impacts and development of adaptive or mitigative strategies. Validation of the models against the observations and establishing the sensitivity to climate change forcing are essential before the model projections are used for assessment of possible impacts. Moreover model simulated climate projections are often of coarse resolution while the models used for impact assessment, (e.g. crop simulation models, or river runoff models etc.) operate on a higher spatial resolution. This spatial mismatch can be overcome by adopting an appropriate strategy of downscaling the GCM output.   This study examines two AOGCM (ECHAM4/OPYC3 and HadCM2) climate change simulations for their performance in the simulation of monsoon climate over India and the sensitivity of the simulated monsoon climate to transient changes in the atmospheric concentrations of greenhouse gases and sulfate aerosols. The results show that the two models simulate the gross features of climate over India reasonably well. However the inter-model differences in simulation of mean characteristics, sensitivity to forcing and in the simulation of climate change suggest need for caution. Further an empirical downscaling approach in used to assess the possibility of using GCM projections for preparation of regional climate change scenario for India.


2016 ◽  
Vol 29 (10) ◽  
pp. 3831-3840 ◽  
Author(s):  
M. Matsueda ◽  
A. Weisheimer ◽  
T. N. Palmer

Abstract In earlier work, it was proposed that the reliability of climate change projections, particularly of regional rainfall, could be improved if such projections were calibrated using quantitative measures of reliability obtained by running the same model in seasonal forecast mode. This proposal is tested for fast atmospheric processes (such as clouds and convection) by considering output from versions of the same atmospheric general circulation model run at two different resolutions and forced with prescribed sea surface temperatures and sea ice. Here output from the high-resolution version of the model is treated as a proxy for truth. The reason for using this approach is simply that the twenty-first-century climate change signal is not yet known and, hence, no climate change projections can be verified using observations. Quantitative assessments of reliability of the low-resolution model, run in seasonal hindcast mode, are used to calibrate climate change time-slice projections made with the same low-resolution model. Results show that the calibrated climate change probabilities are closer to the proxy truth than the uncalibrated probabilities. Given that seasonal forecasts are performed operationally already at several centers around the world, in a seamless forecast system they provide a resource that can be used without cost to help calibrate climate change projections and make them more reliable for users.


2015 ◽  
Vol 6 (3) ◽  
pp. 596-614 ◽  
Author(s):  
Proloy Deb ◽  
Anthony S. Kiem ◽  
Mukand S. Babel ◽  
Sang Thi Chu ◽  
Biplab Chakma

This study evaluates the impacts of climate change on rainfed maize (Zea mays) yield and evaluates different agro-adaptation measures to counteract its negative impacts at Sikkim, a Himalayan state of India. Future climate scenarios for the 10 years centered on 2025, 2055 and 2085 were obtained by downscaling the outputs of the HadCM3 General Circulation Model (GCM) under for A2 and B2 emission scenarios. HadCM3 was chosen after assessing the performance analysis of six GCMs for the study region. The daily maximum and minimum temperatures are projected to rise in the future and precipitation is projected to decrease (by 1.7 to 22.6% relative to the 1991–2000 baseline) depending on the time period and scenarios considered. The crop simulation model CERES-Maize was then used to simulate maize yield under future climate change for the future time windows. Simulation results show that climate change could reduce maize productivity by 10.7–18.2%, compared to baseline yield, under A2 and 6.4–12.4% under B2 scenarios. However, the results also indicate that the projected decline in maize yield could be offset by early planting of seeds, lowering the farm yard manure application rate, introducing supplementary irrigation and shifting to heat tolerant varieties of maize.


2019 ◽  
Vol 20 (8) ◽  
pp. 1635-1647 ◽  
Author(s):  
Cristián Chadwick ◽  
Jorge Gironás ◽  
Sebastián Vicuña ◽  
Francisco Meza

Abstract The time at which climate change signal can be clearly distinguished from noise is known as time of emergence (ToE) and is typically detected by a general circulation model (GCM) signal-to-noise ratio exceeding a certain threshold. ToE is commonly estimated at large scales from GCMs, although management decisions and adaptation strategies are implemented locally. This paper proposes a methodology to estimate ToE for both precipitation and temperature at local scales (i.e., river basin). The methodology considers local climatic conditions and unbiased GCM projections to estimate ToE by using the statistical power to find when the climate significantly differs from the historical one. The method suggests that ToE for temperature already occurred in three Chilean basins (Limarí, Maipo, and Maule). However, in terms of precipitation, an earlier ToE is clearly identified for the Maule basin, indicating that risk assessment and adaptation measures should be implemented first in this basin.


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