Drought Forecasting in a Semi-arid Watershed Using Climate Signals:a Neuro-fuzzy Modeling Approach

Large-scale annual climate indices were used to forecast annual drought conditions in the Maharlu-Bakhtegan watershed,located in Iran,using a neuro-fuzzy model.The Standardized Precipitation Index(SPI) was used as a proxy for drought conditions.Among the 45 climate indices considered,eight identified as most relevant were the Atlantic Multidecadal Oscillation(AMO),Atlantic Meridional Mode(AMM),the Bivariate ENSO Time series(BEST),the East Central Tropical Pacific Surface Temperature(NINO 3.4),the Central Tropical Pacific Surface Temperature(NINO 4),the North Tropical Atlantic Index(NTA),the Southern Oscillation Index(SOI),and the Tropical Northern Atlantic Index(TNA).These indices accounted for 81% of the variance in the Principal Components Analysis(PCA) method.The Atlantic surface temperature(SST:Atlantic) had an inverse relationship with SPI,and the AMM index had the highest correlation.Drought forecasts of neuro-fuzzy model demonstrate better prediction at a two-year lag compared to a stepwise regression model.

North Atlantic Abrupt Climate Signals during the Last Glacial Period in Central Asia：Evidences from Aeolian Loess Sediments

Objective Climate fluctuations over suborbital or millennial timescale display significant instability during the last glacial period,which are often superimposed upon the orbital periodicity.They triggered some abrupt climate events,

Identifying Possible Climate Change Signals Using Meteorological Parameters in Short-Term Fire Weather Variability for Russian Boreal Forest in the Republic of Sakha (Yakutia)

The Boreal forest is a terrestrial ecosystem highly vulnerable to the impacts of short-term climate and weather variabilities. Detecting abrupt, rapid climate-induced changes in fire weather and related changes in fire seasonality can provide important insights to assessing impacts of climate change on forestry. This paper, taking the Sakha Republic of Russia as study area, aims to suggest an approach for detecting signals indicating climate-induced changes in fire weather to express recent fire weather variability by using short-term ranks of major meteorological parameters such as air temperature and atmospheric precipitation. Climate data from the “Global Summary of the Day Product” of NOAA (the United States National Oceanic and Atmospheric Administration) for 1996 to 2018 were used to investigate meteorological parameters that drive fire activity. The detection of the climate change signals is made through a 4-step analysis. First, we used descriptive statistics to grasp monthly, annual, seasonal and peak fire period characteristics of fire weather. Then we computed historical normals for WMO reference period, 1961-1990, and the most recent 30-year period for comparison with the current means. The variability of fire weather is analyzed using standard deviation, coefficient of variation, percentage departures from historical normals, percentage departures from the mean, and precipitation concentration index. Inconsistency and abrupt changes in the evolution of fire weather are assessed using homogeneity analysis whilst a Mann-Kendall test is used to detect significant trends in the time series. The results indicate a significant increase of temperature during spring and fall months, which extends the fire season and potentially contributes to increase of burned areas. We again detected a significant rainfall shortage in September which extended the fire season. Furthermore, this study suggests a new approach in statistical methods appropriate for the detection of climate change signals on fire weather variability using short-term climate ranks and evaluation of its impact on fire seasonality and activity.

Growth response of Abies spectabilis to climate along an elevation gradient of the Manang valley in the central Himalayas

The Himalayas are characterized by a broad gradient of bioclimatic zones along their elevation.However,less is known how forest growth responds to climatic change along elevation.In this study,four standard treering width chronologies of Himalayan fir(Abies spectabilis)were developed,spanning 142–649 years along an elevation gradient of 3076–3900 m a.s.l.Principal component analysis classified the four chronologies into two groups;the ones at lower elevations(M1 and M2)and higher elevations(M3 and M4)show two distinct growth trends.Radial growth is limited by summer(June–August)precipitation at M3,and by precipitation during spring(March–May)and summer at M4.It is limited by spring temperatures and winter precipitation(December–February)at M1.Tree-ring width chronologies also significantly correlate with winter and spring Palmer Drought Severity Index(PDSI)at M1,and with summer PDSI at M3 and M4.Thus,Himalayan fir growth at high elevations is mainly limited by moisture stress rather than by low temperatures.Furthermore,the occurrence of missing rings coincides with dry periods,providing additional evidence for moisture limitation of Himalayan fir growth.

ESTIMATES OF CLIMATE NOISES OF ANNUAL MEAN TEMPERATURES OVER CHINA

In this paper,a design to estimate climate noise of annual mean temperature has been made by means of the mini- mum interannual variance and effectively independent observations in time series.By using it the climate noises of annu- al mean surface air temperatures have been estimated based on the data from 1960 to 1991 in this country.The low val- ues of climate noises of annual mean temperatures are found in the southeastern Tibet Plateau,Yunnan,the Sichuan Ba- sin and south of the middle and lower reaches of the Changjiang River Valley.The high values are seen in the northwestern and northeastern China and the rest of the Tibet Plateau.A relatively low value region is in the southern Xinjiang.

保持土壤湿度对减缓气候变化重要性

A troubling feedback loop, where drier soil contributes to hotter climates, has been widely recognized.This study, drawing on climate model simulations, reveals that maintaining current global soil moisture levels could significantly alleviate 32.9% of land warming under low-emission scenarios. This action could also postpone reaching critical warming thresholds of 1.5 °C and 2.0 °C by at least a decade. Crucially,preserving soil moisture at current levels could prevent noticeable climate change impacts across 42%of the Earth's land, a stark deviation from projections suggesting widespread impacts before the 2060s.To combat soil drying, afforestation in mid-to-low latitude regions within the next three decades is proposed as an effective strategy to increase surface water availability. This underscores the substantial potential of nature-based solutions for managing soil moisture, benefiting both climate change mitigation and ecological enhancement.

RECONSTRUCTION OF WIND STRESS ANOMALIES SIMULATED BY AN AGCM USING SVD TECHNIQUE

Systematic errors in the COLA R15 AGCM are analyzed by the SVD technique.In order to remove or reduce this kind of error source and reduce climate drift in coupled runs a way in which the wind stress anomalies simulated by an AGCM are reconstructed is proposed by using SVD anal- ysis.Experimental results show that not only wind stress anomalies simulated by an AGCM are obviously improved by reconstructed wind stress anomalies but also this reconstruction has a func- tion of a low-pass time filter,as a result,response of the ZC ocean model to reconstructed wind stress anomalies is more realistic than that of simulated wind stress anomalies by an AGCM.In this paper,application of the hybrid couple ocean-atmosphere model is further discussed.