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Climate change projections for Tamil Nadu, India: deriving high-resolution climate data by a downscaling approach using PRECIS

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THEORETICAL AND APPLIED CLIMATOLOGY 2016年第3-4期123卷 523-535页

作者： Bal, Prasanta Kumar Ramachandran, A. Geetha, R. Bhaskaran, B. Thirumurugan, P. Indumathi, J. Jayanthi, N. Anna Univ Ctr Climate Change & Adaptat Res Madras 600025 Tamil Nadu India Anna Univ Dept Informat Sci & Technol Madras 600025 Tamil Nadu India Fujitsu Labs Europe Hayes Middx England

In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 A degrees C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 A degrees C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments.

关键词： Climate change Simulation computer based modeling

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Skill of regional and global model forecast over Indian region

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THEORETICAL AND APPLIED CLIMATOLOGY 2016年第3-4期123卷 629-636页

作者： Kumar, Prashant Kishtawal, C. M. Pal, P. K. Space Applicat Ctr ISRO EPSA Atmospher & Ocean Sci Grp Ahmadabad 380015 Gujarat India

The global model analysis and forecast have a significant impact on the regional model predictions, as global model provides the initial and lateral boundary condition to regional model. This study addresses an important question whether the regional model can improve the short-range weather forecast as compared to the global model. The National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) and the Weather Research and Forecasting (WRF) model are used in this study to evaluate the performance of global and regional models over the Indian region. A 24-h temperature and specific humidity forecast from the NCEP GFS model show less error compared to WRF model forecast. Rainfall prediction is improved over the Indian landmass when WRF model is used for rainfall forecast. Moreover, the results showed that high-resolution global model analysis (GFS4) improved the regional model forecast as compared to low-resolution global model analysis (GFS3).

关键词： Analysis Boundary layer computer based modeling Weather forecasting

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Interactions between urbanization, heat stress, and climate change

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CLIMATIC CHANGE 2015年第3-4期129卷 525-541页

作者： Oleson, K. W. Monaghan, A. Wilhelmi, O. Barlage, M. Brunsell, N. Feddema, J. Hu, L. Steinhoff, D. F. Natl Ctr Atmospher Res Boulder CO 80307 USA Univ Kansas Lawrence KS 66045 USA

Heat stress (HS) is a leading cause of weather-related human mortality. As temperatures continue to increase due to climate change, HS is expected to worsen. HS can be magnified in urban areas because of the urban heat island effect. We use an urban canyon model coupled to a land surface model to quantify present-day and projected mid-21st century rural and urban HS for boreal summer over the U.S. and southern Canada and examine the effects of three urban density classes on HS. Five indices of HS are implemented in the model [the NWS Heat Index (HI), Apparent Temperature (AT), Simplified Wet Bulb Globe Temperature, Humidex, and Discomfort Index]. The present-day urban-rural contrast in HS differs according to which index is used. The HI and Humidex have higher urban-rural HS for all density classes than defined by temperature alone. Future urban HS is amplified by 0.5-1.0 A degrees C for the AT, HI, and Humidex compared to temperature alone. For four cities examined in further detail, climate change by mid-century increases the number of high HS days and nights in both rural and urban areas, the magnitude being highly dependent on HS index, urban density class, and each city's climatic setting. Houston exhibits noteworthy mid-century increases in high heat stress nights, with more than half of summer nights qualifying as high HS in not only urban areas but also rural areas, indicating the need to consider vulnerability and adaptive capacity of both rural and urban populations in the context of climate change.

关键词： Climate change Urban areas Temperature Heat computer based modeling

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BioEarth: Envisioning and developing a new regional earth system model to inform natural and agricultural resource management

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CLIMATIC CHANGE 2015年第3-4期129卷 555-571页

作者： Adam, Jennifer C. Stephens, Jennie C. Chung, Serena H. Brady, Michael P. Evans, R. David Kruger, Chad E. Lamb, Brian K. Liu, Mingliang Stoeckle, Claudio O. Vaughan, Joseph K. Rajagopalan, Kirti Harrison, John A. Tague, Christina L. Kalyanaraman, Ananth Chen, Yong Guenther, Alex Leung, Fok-Yan Leung, L. Ruby Perleberg, Andrew B. Yoder, Jonathan Allen, Elizabeth Anderson, Sarah Chandrasekharan, Bhagyam Malek, Keyvan Mullis, Tristan Miller, Cody Nergui, Tsengel Poinsatte, Justin Reyes, Julian Zhu, Jun Choate, Janet S. Jiang, Xiaoyan Nelson, Roger Yoon, Jin-Ho Yorgey, Georgine G. Johnson, Kristen Chinnayakanahalli, Kiran J. Hamlet, Alan F. Nijssen, Bart Walden, Von Washington State Univ Pullman WA 99164 USA Clark Univ Worcester MA 01610 USA Washington State Univ Wenatchee WA USA Washington State Univ Vancouver WA USA Univ Calif Santa Barbara Santa Barbara CA 93106 USA Oregon State Univ Corvallis OR 97331 USA Pacific NW Natl Lab Richland WA 99352 USA Natl Ctr Atmospher Res Boulder CO 80307 USA Washington State Univ Seattle WA USA AIRWorldwide Boston MA USA Notre Dame Univ Notre Dame IN USA Univ Washington Seattle WA 98195 USA

As managers of agricultural and natural resources are confronted with uncertainties in global change impacts, the complexities associated with the interconnected cycling of nitrogen, carbon, and water present daunting management challenges. Existing models provide detailed information on specific sub-systems (e.g., land, air, water, and economics). An increasing awareness of the unintended consequences of management decisions resulting from interconnectedness of these sub-systems, however, necessitates coupled regional earth system models (EaSMs). Decision makers' needs and priorities can be integrated into the model design and development processes to enhance decision-making relevance and "usability" of EaSMs. BioEarth is a research initiative currently under development with a focus on the U.S. Pacific Northwest region that explores the coupling of multiple stand-alone EaSMs to generate usable information for resource decision-making. Direct engagement between model developers and non-academic stakeholders involved in resource and environmental management decisions throughout the model development process is a critical component of this effort. BioEarth utilizes a bottom-up approach for its land surface model that preserves fine spatial-scale sensitivities and lateral hydrologic connectivity, which makes it unique among many regional EaSMs. This paper describes the BioEarth initiative and highlights opportunities and challenges associated with coupling multiple stand-alone models to generate usable information for agricultural and natural resource decision-making.

关键词： Climate change Agriculture computer based modeling

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Impact of Atlantic SST and high frequency atmospheric variability on the 1993 and 2008 Midwest floods: Regional climate model simulations of extreme climate events

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CLIMATIC CHANGE 2015年第3-4期129卷 397-411页

作者： Patricola, Christina M. Chang, Ping Saravanan, R. Texas A&M Univ Dept Atmospher Sci College Stn TX 77843 USA Texas A&M Univ Dept Oceanog College Stn TX 77843 USA Ocean Univ China Phys Oceanog Lab Qingdao Peoples R China

The role of sea surface temperature anomalies (SSTAs) in the Atlantic and eastern Pacific and high-frequency atmospheric variability from the Pacific during the 1993 and 2008 Midwest floods is investigated with a regional climate model. The SSTAs insignificantly modulate Midwest rainfall during the 1993 flood, but enhance precipitation during the 2008 peak flood by strengthening the southern portion of the Great Plains low-level jet, enhancing moisture transport from the Gulf of Mexico into the Midwest. This work suggests that while North Atlantic SST strongly controls Midwest decadal drought and pluvial periods, it plays a minimal or secondary role in modulating extreme flood events lasting weeks to months. A negative Pacific/North American (PNA) teleconnection marked the peak of both floods, suggesting a link between extreme Midwest warm season rainfall and high-frequency PNA variations. Simulations that apply a 10-day low-pass filter to the western lateral boundary condition indicate that interactions between the eddy and time-mean flow played a significant, but counterintuitive role, during the 1993 flood. Although above normal Pacific cyclone activity was observed to trigger heavy Midwest precipitation, the synoptic eddies also indirectly influenced rainfall by modifying the time-mean circulation. Simulations show that eddies from the Pacific dampened the positive rainfall anomalies by weakening vertically integrated moisture transport and upper level divergence anomalies over the Midwest.

关键词： Climate change Atmosphere Floods Simulation computer based modeling

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Investigating the nexus of climate, energy, water, and land at decision-relevant scales: the Platform for Regional Integrated modeling and Analysis (PRIMA)

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CLIMATIC CHANGE 2015年第3-4期129卷 573-588页

作者： Kraucunas, Ian Clarke, Leon Dirks, James Hathaway, John Hejazi, Mohamad Hibbard, Kathy Huang, Maoyi Jin, Chunlian Kintner-Meyer, Michael van Dam, Kerstin Kleese Leung, Ruby Li, Hong-Yi Moss, Richard Peterson, Marty Rice, Jennie Scott, Michael Thomson, Allison Voisin, Nathalie West, Tristram Pacific NW Natl Lab Richland WA 99352 USA

The Platform for Regional Integrated modeling and Analysis (PRIMA) is an innovative modeling system developed at Pacific Northwest National Laboratory (PNNL) to simulate interactions among natural and human systems at scales relevant to regional decision making. PRIMA brings together state-of-the-art models of regional climate, hydrology, agriculture and land use, socioeconomics, and energy systems using a flexible coupling approach. Stakeholder decision support needs underpin the application of the platform to regional issues, and an uncertainty characterization process is used to identify robust decisions. The platform can be customized to inform a variety of complex questions, such as how a policy in one sector might affect the ability to meet climate mitigation targets or adaptation goals in another sector. Current numerical experiments focus on the eastern United States, but the framework is designed to be regionally flexible. This paper provides a high-level overview of PRIMA's functional capabilities and describes some key challenges and opportunities associated with integrated regional modeling.

关键词： Climate change computer based modeling Hydrology

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Calibration and validation of lake surface temperature simulations with the coupled WRF-lake model

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CLIMATIC CHANGE 2015年第3-4期129卷 471-483页

作者： Gu, Hongping Jin, Jiming Wu, Yihua Ek, Michael B. Subin, Zachary M. Chinese Acad Sci Inst Atmospher Phys Key Lab Reg Climate Environm Res Temperate East A Beijing Peoples R China Utah State Univ Dept Watershed Sci & Plants Logan UT 84341 USA Utah State Univ Dept Soils Logan UT 84341 USA Utah State Univ Dept Climate Logan UT 84341 USA NOAA Environm Modeling Ctr Natl Ctr Environm Predict Natl Weather Serv Camp Springs MD USA Princeton Univ Princeton Environm Inst Princeton NJ 08544 USA

A one-dimensional (1-D) physically based lake model was coupled to the Weather Research and Forecasting (WRF) model version 3.2 developed by the National Center for Atmospheric Research to dynamically simulate physical processes of lakes and their effects on weather and climate at local and regional scales. Our study area is focused on the Great Lakes. This coupled model realistically reproduces the lake surface temperature (LST) at a buoy station in a shallow lake (Lake Erie) while generating strong LST biases ranging from -20 to 20 A degrees C at a buoy station in a deep lake (Lake Superior). Through many sensitivity tests, we find that the biases in the deep lake LST simulations result from the drastic underestimation of heat transfer between the lower and upper parts of the lake through unrealistic eddy diffusion. Additional tests were made to calibrate the eddy diffusivity in WRF-Lake. It is found that when this parameter is multiplied by a factor ranging from 10(2) to 10(5) for various lake depths deeper than 15 m, the LST simulations for the deep lake buoy station show good agreement with observations, and the bias range reduces to +/- 4 A degrees C. Essentially, the enlarged eddy diffusivity strengthens heat transfer within the lake columns in the deep lake, which is significantly underestimated in the lake model without calibration. Validation simulations with the calibrated eddy diffusivity were carried out for the whole of Lake Superior and Lake Erie. The LST simulations still have a substantial bias reduction when compared with those produced with the original eddy diffusivity, indicating that the calibrated parameter is representative. In addition, the improved 1-D lake model with WRF reasonably reproduces the remotely sensed LST geographic distribution.

关键词： Lakes Climate change computer based modeling Simulation Studies

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Multi-scale remote sensing estimates of urban fractions and road widths for regional models

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CLIMATIC CHANGE 2015年第3-4期129卷 543-554页

作者： Jia, Gensuo Xu, Ronghan Hu, Yonghong He, Yuting Chinese Acad Sci Inst Atmospher Phys TEA Beijing 100029 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Ctr Earth Observat & Digital Earth Beijing 100094 Peoples R China Penn State Univ Dept Meteorol University Pk PA 16802 USA

Landuse in East Asia has changed substantially during the last three decades, featured with expansion of urban built-up at unprecedented scale and speed. The fast expansion of urban areas could contribute to local and even regional climate change. However, current spatial datasets of urban fractions do not well represent the extent and expansion of urban areas in the regions, and that best available satellite data and remote sensing techniques have not been well applied to serve regional modeling of urbanization impacts on near surface temperature and other climate variables. Better estimates of localized urban fractions are badly needed. Here we use high and mid resolution satellite data to estimate urban fractions and road width at local and regional scales. With our fractional cover, data fusion, and differentiated threshold approaches, more spatial details of urban cover are demonstrated than previously reported in many global datasets. Many city clusters were merging into each other, with gradual blurring of boundaries and disappearance of gaps among member cities. Cities and towns were more connected with roads and commercial corridors, while wildland and urban green areas have become more isolated as patches among built-up areas. Average road width in commercial areas was 37.2 m in Beijing (north, temperate) and 24.2 m in Guangzhou (south, tropical), which are greater than these listed in model default values. Those new estimates could effectively improve climate simulation at local and regional scales in East Asia.

关键词： Urban areas Climate change computer based modeling

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Use of very high resolution climate model data for hydrological modelling: baseline performance and future flood changes

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CLIMATIC CHANGE 2015年第2期133卷 193-208页

作者： Kay, A. L. Rudd, A. C. Davies, H. N. Kendon, E. J. Jones, R. G. Ctr Ecol & Hydrol Wallingford Oxon England Met Off Hadley Ctr Exeter Devon England

Increasingly, data from Regional Climate Models (RCMs) are used to drive hydrological models, to investigate the potential water-related impacts of climate change, particularly for flood and droughts. Generally, some form of further downscaling of RCM data has been required, but recently the first decadal-length runs of very high resolution RCMs (with convection-permitting scales) have been performed. Here, a set of such runs for southern Britain has been used to drive a gridded hydrological model. Results using a 1.5 km RCM nested in a 12 km RCM driven by European-reanalysis boundary conditions show that the 1.5 km RCM generally performs worse than the 12 km RCM for simulating river flows in 32 example catchments. The clear spatial patterns of bias are consistent with bias patterns shown in the RCM precipitation data. Results using 1.5 and 12 km RCM runs for the current climate and a potential future climate (driven by GCM boundary conditions) show clear differences in projected changes in flood peaks. The 1.5 km RCM tends towards larger increases than the 12 km RCM, particularly in spring and winter. If robust, this could have important consequences for adaptation planning under climate change, but further research is required, particularly given the greater biases in the baseline flow simulations driven by 1.5 km RCM data, and the use of only a single short future climate projection.

关键词： Climate change computer based modeling Floods

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The improvement of a regional climate model by coupling a land surface model with eco-physiological processes: A case study in 1998

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CLIMATIC CHANGE 2015年第3-4期129卷 457-470页

作者： Dan, Li Cao, Fuqiang Gao, Rong Chinese Acad Sci Inst Atmospher Phys Key Lab Reg Climate Environm Temperate East Asia Beijing 100029 Peoples R China China Meteorol Adm Natl Climate Ctr Beijing 100081 Peoples R China

The Atmospheric-Vegetation Interaction Model (AVIM) is coupled with a Regional Integrated Environment modeling System (RIEMS) to improve the regional simulation of climate variables. A case study in 1998 is implemented to study the improvement mechanism through land-air interaction in East Asia, especially in Asian summer monsoon regions. The coupled model reduces the warming bias in July in East China through the surface heat fluxes changes. Compared to the original model of RIEMS, the strong precipitation of eastern China in July is weakened by coupling of the interactive vegetation. The surface heat flux in uncoupled model is remarkably overestimated in these regions, and the enhanced heating from land surface, particularly with latent heat flux in July, will produce the overestimated temperature and precipitation in East China. Through coupling AVIM with RIEMS, the simulated area-averaged latent heat flux of two key regions decreases (e.g. from 132.36 to 103.13 W/m(2) over the region 1 between 105-125A degrees E and 20-40A degrees N) in July, which makes the overestimated temperature and precipitation declined, respectively.

关键词： Case studies Climate change computer based modeling

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