Hugo G. Hidalgo

Bio: Hugo G. Hidalgo is an academic researcher from University of Costa Rica. The author has contributed to research in topics: Climate change & Climate model. The author has an hindex of 35, co-authored 62 publications receiving 9705 citations. Previous affiliations of Hugo G. Hidalgo include University of California, Berkeley & Scripps Institution of Oceanography.

Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity

Abstract: Western United States forest wildfire activity is widely thought to have increased in recent decades, yet neither the extent of recent changes nor the degree to which climate may be driving regional changes in wildfire has been systematically documented. Much of the public and scientific discussion of changes in western United States wildfire has focused instead on the effects of 19th- and 20th-century land-use history. We compiled a comprehensive database of large wildfires in western United States forests since 1970 and compared it with hydroclimatic and land-surface data. Here, we show that large wildfire activity increased suddenly and markedly in the mid-1980s, with higher large-wildfire frequency, longer wildfire durations, and longer wildfire seasons. The greatest increases occurred in mid-elevation, Northern Rockies forests, where land-use histories have relatively little effect on fire risks and are strongly associated with increased spring and summer temperatures and an earlier spring snowmelt.

Human-Induced Changes in the Hydrology of the Western United States

Abstract: Observations have shown that the hydrological cycle of the western United States changed significantly over the last half of the 20th century. We present a regional, multivariable climate change detection and attribution study, using a high-resolution hydrologic model forced by global climate models, focusing on the changes that have already affected this primarily arid region with a large and growing population. The results show that up to 60% of the climate-related trends of river flow, winter air temperature, and snow pack between 1950 and 1999 are human-induced. These results are robust to perturbation of study variates and methods. They portend, in conjunction with previous work, a coming crisis in water supply for the western United States.

Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods

Abstract: Downscaling of climate model data is essential to local and regional impact analysis. We compare two meth- ods of statistical downscaling to produce continuous, grid- ded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km 2 per grid cell) reso- lution over the western U.S. We use NCEP/NCAR Reanaly- sis data from 1950-1999 as a surrogate General Circulation Model (GCM). The two methods included are constructed analogues (CA) and a bias correction and spatial downscal- ing (BCSD), both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA down- scales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to gener- ate daily values. The methods produce generally comparable skill in producing downscaled, gridded fields of precipita- tion and temperatures at a monthly and seasonal level. For daily precipitation, both methods exhibit limited skill in re- producing both observed wet and dry extremes and the dif- ference between the methods is not significant, reflecting the general low skill in daily precipitation variability in the re- analysis data. For low temperature extremes, the CA method produces greater downscaling skill than BCSD for fall and winter seasons. For high temperature extremes, CA demon- strates higher skill than BCSD in summer. We find that the choice of most appropriate downscaling technique depends on the variables, seasons, and regions of interest, on the availability of daily data, and whether the day to day cor- respondence of weather from the GCM needs to be repro-

Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods

Abstract: Downscaling of climate model data is essential to local and regional impact analysis. We compare two meth- ods of statistical downscaling to produce continuous, grid- ded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km 2 per grid cell) reso- lution over the western U.S. We use NCEP/NCAR Reanaly- sis data from 1950-1999 as a surrogate General Circulation Model (GCM). The two methods included are constructed analogues (CA) and a bias correction and spatial downscal- ing (BCSD), both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA down- scales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to gener- ate daily values. The methods produce generally comparable skill in producing downscaled, gridded fields of precipita- tion and temperatures at a monthly and seasonal level. For daily precipitation, both methods exhibit limited skill in re- producing both observed wet and dry extremes and the dif- ference between the methods is not significant, reflecting the general low skill in daily precipitation variability in the re- analysis data. For low temperature extremes, the CA method produces greater downscaling skill than BCSD for fall and winter seasons. For high temperature extremes, CA demon- strates higher skill than BCSD in summer. We find that the choice of most appropriate downscaling technique depends on the variables, seasons, and regions of interest, on the availability of daily data, and whether the day to day cor- respondence of weather from the GCM needs to be repro-

The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California

Abstract: . Three statistical downscaling methods were applied to NCEP/NCAR reanalysis (used as a surrogate for the best possible general circulation model), and the downscaled meteorology was used to drive a hydrologic model over California. The historic record was divided into an "observed" period of 1950–1976 to provide the basis for downscaling, and a "projected" period of 1977–1999 for assessing skill. The downscaling methods included a bias-correction/spatial downscaling method (BCSD), which relies solely on monthly large scale meteorology and resamples the historical record to obtain daily sequences, a constructed analogues approach (CA), which uses daily large-scale anomalies, and a hybrid method (BCCA) using a quantile-mapping bias correction on the large-scale data prior to the CA approach. At 11 sites we compared three simulated daily flow statistics: streamflow timing, 3-day peak flow, and 7-day low flow. While all downscaling methods produced reasonable streamflow statistics at most locations, the BCCA method consistently outperformed the other methods, capturing the daily large-scale skill and translating it to simulated streamflows that more skillfully reproduced observationally-driven streamflows.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Climate Change 2007: Impacts, Adaptation and Vulnerability.

Abstract: Impatti, adattamento e vulnerabilita Le cause e le responsabilita dei cambiamenti climatici sono state trattate sul numero di ottobre della rivista Cda. Approfondiamo l’argomento presentando il documento: “Cambiamenti climatici 2007: impatti, adattamento e vulnerabilita” votato ad aprile 2007 dal secondo gruppo di lavoro del Comitato Intergovernativo sui Cambiamenti Climatici (Intergovernmental Panel on Climate Change). Si tratta del secondo di tre documenti che compongono il quarto rapporto sui cambiamenti climatici.

Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought?

Abstract: Summary Severe droughts have been associated with regional-scale forest mortality worldwide. Climate change is expected to exacerbate regional mortality events; however, pre- diction remains difficult because the physiological mechanisms underlying drought survival and mortality are poorly understood. We developed a hydraulically based theory considering carbon balance and insect resistance that allowed development and examination of hypotheses regarding survival and mortality. Multiple mechanisms may cause mortality during drought. A common mechanism for plants with isohydric