Wangt, Y., He, B., Herath, S., Basnayake, S., & Huang, W. (2014). Climate Change Scenarios Analysis in Coastal Region of Thailand. Journal of Coastal Research, 68, 160–167.
Abstract: The impact of climate change is estimated to be particularly severe in many developing countries, including the coastal zones prone to flooding and drought. As a coastal region, Thailand has been affected by climate change significantly in terms of temperature and rainfall distribution change. In this study, a downscaling study was carried out to identify some climate-related planning parameters for the representative cities in Thailand using the regional climate model. Results indicated that in the study area around the Hat Yai the near future atmosphere temperature will increase about 1 °C to 1.5 °C compared to the present condition. The minimum annual temperature will increase about 0.8 degree from 23 °C to 23.8 °C. It is ranging between 20.8 °C–25 °C. The maximum annual temperature in Hat Yai will increase about 1 degree from 32.6 °C to 33.6 °C. The mean annual temperature will increase about 1 degree from 27.8 °C to 28.8 °C. The temperature will increase largely in summer and rainy season in the future. The near future rainfall is projected to increase in most of seasons, especially during the rainy season which will bring more risk for flood disaster. Furthermore, rainfall pattern and distribution will be also changed in the near future in Songkhla, with more rain to be expected in rainy season.
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Webber, H., White, J. W., Kimball, B. A., Ewert, F., Asseng, S., Eyshi Rezaei, E., et al. (2018). Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions. Field Crops Research, 216, 75–88.
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Weihs, R. R., & Bourassa, M. A. (2014). Modeled diurnally varying sea surface temperatures and their influence on surface heat fluxes. J. Geophys. Res. Oceans, 119(7), 4101–4123.
Abstract: A diurnal warming model is used to create a new data set of global, diurnally varying sea surface temperatures (dSSTs) and surface turbulent heat fluxes over a 5 year period. The magnitude of diurnal warming is primarily a function of low wind speed and net heat flux. Differences between each of the surface turbulent fluxes with and without a diurnally varying SST are examined on hourly, daily, and seasonal time scales. Over a 2 month period, maximum averaged diurnal warming is as large as 0.3°C, and latent heat flux is underestimated by as much as 8 W/m2 in the Indian Ocean. They also exceed roughly 0.7°C and 10 W/m2, respectively, up to 25% of the total daytime in the Atlantic. A best-case approach validation shows the model overestimates peak warming and underestimates the duration of the cycle, though the average error is quite small. The model is tested under a variety of wind speed, solar radiation, and precipitation conditions to examine the impact of potential biases or error in the input data. To test the impact of a positive bias in the wind speeds, diurnal warming magnitudes are recomputed with an adjusted wind under near-neutral conditions. Compared to the original data, diurnal warming can increase by as much as 1.5°C on an hourly scale but generally is <0.06°C. Although precipitation effects on dSSTs are small compared to winds and radiation, the model configuration wrongly causes diurnal warming to increase by precipitation, contrary to the underlying model physics.
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Woodcroft, B. J., Singleton, C. M., Boyd, J. A., Evans, P. N., Emerson, J. B., Zayed, A. A. F., et al. (2018). Genome-centric view of carbon processing in thawing permafrost. Nature, 560(7716), 49–+.
Abstract: As global temperatures rise, large amounts of carbon sequestered in permafrost are becoming available for microbial degradation. Accurate prediction of carbon gas emissions from thawing permafrost is limited by our understanding of these microbial communities. Here we use metagenomic sequencing of 214 samples from a permafrost thaw gradient to recover 1,529 metagenome-assembled genomes, including many from phyla with poor genomic representation. These genomes reflect the diversity of this complex ecosystem, with genus-level representatives for more than sixty per cent of the community. Meta-omic analysis revealed key populations involved in the degradation of organic matter, including bacteria whose genomes encode a previously undescribed fungal pathway for xylose degradation. Microbial and geochemical data highlight lineages that correlate with the production of greenhouse gases and indicate novel syntrophic relationships. Our findings link changing biogeochemistry to specific microbial lineages involved in carbon processing, and provide key information for predicting the effects of climate change on permafrost systems.
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Wu, D., Chen, X., Lv, F., Brenner, M., Curtis, J., Zhou, A., et al. (2018). Decoupled early Holocene summer temperature and monsoon precipitation in southwest China. Quaternary Science Reviews, 193, 54–67.
Abstract: Proxy-based reconstructions of Holocene temperature show that both the timing and magnitude of the thermal maximum varied substantially across different regions. Given the 'Holocene temperature conundrum', it is becoming increasingly important to reconstruct seasonal temperature variations. As a major component of the global monsoon system, the Indian summer monsoon (ISM) transports moisture and heat from the tropical oceans to higher latitudes and thus it has substantial socioeconomic implications for its regions of influences. We developed a well-dated, pollen-based summer temperature record (mean July; MJT) for the last 14,000 years from Xingyun Lake in southwest China, where the climate is dominated by the ISM. MJT decreased during the Younger Dryas, increased slowly to high values during 8000-5500/yr BP, and decreased thereafter. The MJT record differs from that inferred using carbonate oxygen isotopes (δ18 O) from the same sediment core. The latter record reflects variations in monsoon precipitation, with highest precipitation during the early Holocene (11,000-6500/yr BP). We propose that summer temperature and precipitation in southwest China were decoupled during the early Holocene. Both MJT and monsoon precipitation decreased after the middle Holocene, tracking the trend in boreal summer insolation. We suggest that greater cloud cover, associated with high precipitation and generated by a strong summer monsoon, may have depressed early Holocene temperatures that would otherwise be driven by greater summer insolation. Melting ice sheets in high-latitude regions and high concentrations of atmospheric aerosols during the early Holocene may also have contributed, in part, to the relatively cool summer temperatures.
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Wurl, O., Bird, K., Cunliffe, M., Landing, W. M., Miller, U., Mustaffa, N. I. H., et al. (2018). Warming and Inhibition of Salinization at the Ocean's Surface by Cyanobacteria. Geophys Res Lett, 45(9), 4230–4237.
Abstract: This paper describes high-resolution in situ observations of temperature and, for the first time, of salinity in the uppermost skin layer of the ocean, including the influence of large surface blooms of cyanobacteria on those skin properties. In the presence of the blooms, large anomalies of skin temperature and salinity of 0.95 degrees C and -0.49 practical salinity unit were found, but a substantially cooler (-0.22 degrees C) and saltier skin layer (0.19 practical salinity unit) was found in the absence of surface blooms. The results suggest that biologically controlled warming and inhibition of salinization of the ocean's surface occur. Less saline skin layers form during precipitation, but our observations also show that surface blooms of Trichodesmium sp. inhibit evaporation decreasing the salinity at the ocean's surface. This study has important implications in the assessment of precipitation over the ocean using remotely sensed salinity, but also for a better understanding of heat exchange and the hydrologic cycle on a regional scale.
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Xu, X., Chassignet, E. P., & Wang, F. (2019). On the variability of the Atlantic meridional overturning circulation transports in coupled CMIP5 simulations. Clim Dyn, 52(11), 6511–6531.
Abstract: The Atlantic meridional overturning circulation (AMOC) plays a fundamental role in the climate system, and long-term climate simulations are used to understand the AMOC variability and to assess its impact. This study examines the basic characteristics of the AMOC variability in 44 CMIP5 (Phase 5 of the Coupled Model Inter-comparison Project) simulations, using the 18 atmospherically-forced CORE-II (Phase 2 of the Coordinated Ocean-ice Reference Experiment) simulations as a reference. The analysis shows that on interannual and decadal timescales, the AMOC variability in the CMIP5 exhibits a similar magnitude and meridional coherence as in the CORE-II simulations, indicating that the modeled atmospheric variability responsible for AMOC variability in the CMIP5 is in reasonable agreement with the CORE-II forcing. On multidecadal timescales, however, the AMOC variability is weaker by a factor of more than 2 and meridionally less coherent in the CMIP5 than in the CORE-II simulations. The CMIP5 simulations also exhibit a weaker long-term atmospheric variability in the North Atlantic Oscillation (NAO). However, one cannot fully attribute the weaker AMOC variability to the weaker variability in NAO because, unlike the CORE-II simulations, the CMIP5 simulations do not exhibit a robust NAO-AMOC linkage. While the variability of the wintertime heat flux and mixed layer depth in the western subpolar North Atlantic is strongly linked to the AMOC variability, the NAO variability is not.
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Yang, Y., Ren, R., Cai, M., & Rao, J. (2015). Attributing analysis on the model bias in surface temperature in the climate system model FGOALS-s2 through a process-based decomposition method. Adv. Atmos. Sci., 32(4), 457–469.
Abstract: This study uses the coupled atmosphere-surface climate feedback-response analysis method (CFRAM) to analyze the surface temperature biases in the Flexible Global Ocean-Atmosphere-Land System model, spectral version 2 (FGOALS-s2) in January and July. The process-based decomposition of the surface temperature biases, defined as the difference between the model and ERA-Interim during 1979–2005, enables us to attribute the model surface temperature biases to individual radiative processes including ozone, water vapor, cloud, and surface albedo; and non-radiative processes including surface sensible and latent heat fluxes, and dynamic processes at the surface and in the atmosphere. The results show that significant model surface temperature biases are almost globally present, are generally larger over land than over oceans, and are relatively larger in summer than in winter. Relative to the model biases in non-radiative processes, which tend to dominate the surface temperature biases in most parts of the world, biases in radiative processes are much smaller, except in the sub-polar Antarctic region where the cold biases from the much overestimated surface albedo are compensated for by the warm biases from nonradiative processes. The larger biases in non-radiative processes mainly lie in surface heat fluxes and in surface dynamics, which are twice as large in the Southern Hemisphere as in the Northern Hemisphere and always tend to compensate for each other. In particular, the upward/downward heat fluxes are systematically underestimated/overestimated in most parts of the world, and are mainly compensated for by surface dynamic processes including the increased heat storage in deep oceans across the globe.
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Yue, Y., Zhou, Y., Wang, J. 'ai, & Ye, X. (2016). Assessing Wheat Frost Risk with the Support of GIS: An Approach Coupling a Growing Season Meteorological Index and a Hybrid Fuzzy Neural Network Model. Sustainability, 8(12), 1308.
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Zhang, F., Zhang, H., Hagen, S. C., Ye, M., Wang, D., Gui, D., et al. (2015). Snow cover and runoff modelling in a high mountain catchment with scarce data: effects of temperature and precipitation parameters. Hydrol. Process., 29(1), 52–65.
Abstract: Snowmelt is an important source of runoff in high mountain catchments. Snowmelt modelling for alpine regions remains challenging with scarce gauges. This study simulates the snowmelt in the Karuxung River catchment in the south Tibetan Plateau using an altitude zone based temperature-index model, calibrates the snow cover area and runoff simulation during 2003�2005 and validates the model performance via snow cover area and runoff simulation in 2006. In the snowmelt and runoff modelling, temperature and precipitation are the two most important inputs. Relevant parameters, such as critical snow fall temperature, temperature lapse rate and precipitation gradient, determine the form and amount of precipitation and distribution of temperature and precipitation in hydrological modelling of the sparsely gauged catchment. Sensitivity analyses show that accurate estimation of these parameters would greatly help in improving the snowmelt simulation accuracy, better describing the snow-hydrological behaviours and dealing with the data scarcity at higher elevations. Specifically, correlation between the critical snow fall temperature and relative humidity and seasonal patterns of both the temperature lapse rate and the precipitation gradient should be considered in the modelling studies when precipitation form is not logged and meteorological observations are only available at low elevation. More accurate simulation of runoff involving snowmelt, glacier melt and rainfall runoff will improve our understanding of hydrological processes and help assess runoff impacts from a changing climate in high mountain catchments.
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Zhang, W., & Kirtman, B. (2019). Estimates of Decadal Climate Predictability From an Interactive Ensemble Model. Geophys. Res. Lett., 46(6), 3387–3397.
Abstract: Decadal climate predictability has received considerable scientific interest in recent years, yet the limits and mechanisms for decadal predictability are currently not well known. It is widely accepted that noise due to internal atmospheric dynamics at the air-sea interface influences predictability. The purpose of this paper is to use the interactive ensemble (IE) coupling strategy to quantify how internal atmospheric noise at the air-sea interface impacts decadal predictability. The IE technique can significantly reduce internal atmospheric noise and has proven useful in assessing seasonal-to-interannual variability and predictability. Here we focus on decadal timescales and apply the nonlinear local Lyapunov exponent method to the Community Climate System Model comparing control simulations with IE simulations. This is the first time the nonlinear local Lyapunov exponent has been applied to the state-of-the-art coupled models. The global patterns of decadal predictability are discussed from the perspective of internal atmospheric noise and ocean dynamics.
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Zhao, C., Liu, B., Piao, S., Wang, X., Lobell, D. B., Huang, Y., et al. (2017). Temperature increase reduces global yields of major crops in four independent estimates. Proc Natl Acad Sci USA, 114(35), 9326–9331.
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