A Trend towards a Stable Warm and Windless State of the Surface Weather Conditions in Northern and Northeastern China during 1961–2014

This study investigates the trends in the mean state and the day-to-day variability （DDV） of the surface weather conditions over northern and northeastern China （NNEC） during 1961-2014 using CN05.1 observational data. In this study, we show that the surface temperature （wind speed） has increased （decreased） over NNEC and that the DDV of the surface temperatures and wind speeds has decreased, indicating a trend towards a stable warm and windless state of the surface weather conditions over NNEC. This finding implies a trend towards more persistent hot and windless episodes, which threaten human health and aggravate environmental problems. The trends are also examined in reanalysis data. Both the ERA-40 and the NCEP data show an increasing （decreasing） trend in the mean state of the surface temperatures （wind speeds）. However, the reanalysis data show a consistent decreasing trend in the DDV of the surface weather conditions only in the spring. The underlying reason for the decreased DDV of the surface weather conditions is further analyzed, focusing on the spring season. Essentially, the decreased DDV of the surface weather conditions can be attributed to a decrease in synoptic-scale wave activity, which is caused by a decrease in the baroclinic instability. There is a contrasting change in the baroclinic instability over East Asia, showing a decreasing （increasing） trend north （south） of 40°N. This contrasting change in the baroclinic instability is primarily caused by a tropospheric cooling zone over East Asia at approximately 40°N, which influences the meridional temperature gradient over East Asia.

Detecting Climate Change in Using Extreme Data from Two Surface Weather Stations: Case Study Valle of Comitan and La Esperanza, Chiapas, Mexico

The study area is located between the cities of Comitan (16°10'43"N and 92°04'20''W) a city with 150,000 inhabitants and La Esperanza (16°9'15''N and 91°52'5''W) a town with 3000 inhabitants. Both weather stations are 30 km from each other in the Chiapas State, México. 54 years of daily records of the series of maximum (tmax) and minimum temperatures (tmin) of the weather station 07205 Comitan that is on top of a house and 30 years of daily records of the weather station 07374 La Esperanza were analyzed. The objective is to analyze the evidence of climate change in the Comitan valley. 2.07% and 19.04% of missing data were filled, respectively, with the WS method. In order to verify homogeneity three methods were used: Standard Normal Homogeneity Test (SNHT), the Von Neumann method and the Buishand method. The heterogeneous series were homogenized using climatol. The trends of tmax and tmin for both weather stations were analyzed by simple linear regression, Sperman’s rho and Mann-Kendall tests. The Mann-Kendal test method confirmed the warming trend at the Comitan station for both variables with ZMK statistic values equal to 1.57 (statistically not significant) and 4.64 (statistically significant). However, for the Esperanza station, it determined a cooling trend for tmin and a slight non-significant warming for tmax with a ZMK statistic of -2.27 (statistically significant) and 1.16 (statistically not significant), for a significance level α = 0.05.

An Intermediate Reference Datum Static Correction Technique and Its Applications

Static corrections using the conventional method are basically conducted in two steps, the weathering correction followed by the correction from the top of the sub-weathering to the unified datum. However, the conventional method fails to well deal with statics problems in case the top of the sub-weathering is sharply undulated and the lateral velocity of the sub-weathering varies significantly. This brings us to the introduction of a smooth intermediate reference datum （IRD） located under the top of the sub-weathering, which helps to further increase the accuracy of statics based on the weathering corrections, and ensures the imaging quality. Good results based on the IRD technique have been achieved in the complex areas in western China. This paper discusses the IRD functions, its application requirements, and selection of related parameters. Some typical sections for comparison are also given in this paper.

Comparison of surface water chemistry and weathering effects of two lake basins in the Changtang Nature Reserve,China

The geochemistry of natural waters in the Changtang Nature Reserve,northern Tibet,can help us understand the geology of catchments,and provide additional insight in surface processes that influence water chemistry such as rock weathering on the Qinghai–Tibet Plateau.However,severe natural conditions are responsible for a lack of scientific data for this area.This study represents the first investigation of the chemical composition of surface waters and weathering effects in two lake basins in the reserve（Lake Dogaicoring Qiangco and Lake Longwei Co）.The results indicate that total dissolved solids（TDS）in the two lakes are significantly higher than in other gauged lakes on the Qinghai–Tibet Plateau,reaching 20–40 g/L,and that TDS of the tectonic lake（Lake Dogaicoring Qiangco）is significantly higher than that of the barrier lake（Lake Longwei Co）.Na＋and Cl-are the dominant ions in the lake waters as well as in the glacier-fed lake inflows,with chemical compositions mainly affected by halite weathering.In contrast,ion contents of inflowing rivers fed by nearby runoff are lower and concentrations of dominant ions are not significant.Evaporite,silicate,and carbonate weathering has relatively equal effects on these rivers.Due to their limited scope,small streams near the lakes are less affected by carbonate than by silicate weathering.

Quality Control and Analysis of Global Gauge-Based Daily Precipitation Dataset from 1980 to 2009

A series of quality control(QC) procedures were performed on a gauge-based global daily precipitation dataset from the Global Telecommunication System(GTS) for the period 1980-2009.A new global daily precipitation(NGDP) dataset was constructed by applying those QC procedures to eliminate erroneous records.The NGDP dataset was evaluated using the NOAA Climate Prediction Center Merged Analysis of Precipitation(CMAP) and the Global Precipitation Climatology Project(GPCP) precipitation datasets.The results showed that the frequency distribution and spatial distribution pattern of NGDP had a nice match with those from the CMAP and GPCP datasets.The global mean correlation coefficients with the CMAP and GPCP data increased from 0.24 for original GTS precipitation data to about 0.70 for NGDP data.Correspondingly,the root mean square errors(RMSE) decreased from 12 mm per day to 1 mm per day.The interannual variabilities of NGDP monthly precipitation are consistent with the CMAP and GPCP datasets in Asia.Meanwhile,the seasonal variabilities for most land areas on the Earth of NGDP dataset are also consistent with the CMAP and GPCP precipitation products.

Estimation of Winds at Different Isobaric Levels Based on the Observed Winds at 850 hPa Level Using Double Fourier Series

A technique based on the double Fourier series is developed to estimate the winds at different isobaric levels forthe limited area domain, 35°E to 140°E and 30°S to 40°N, using the observed winds at 850 hPa lcvcl for the month ofJune. For this purpose the wind field at a level under consideration is taken in the ratio form with that of 850 hPa level and the coefficients of the double Fouricr series are computed. These coefficients are subsequently used to computethe winds which are compared with the actual winds. The results of the double Fourier series technique are comparedwith those of the polynomial surface fitting method developed by Bavadekar and Khaladkar (1 992). The technique isalso applied for the daily wind data of 11. June, 1979 and the validation of the technique is tested for a few radiosondestations of india. The computed winds for these radiosonde stations arc quite close to observed winds.

Surface Weather Parameters Forecasting Using Analog Ensemble Method over the Main Airports of Morocco

Surface weather parameters detain high socioeconomic impact and strategic insights for all users,in all domains(aviation,marine traffic,agriculture,etc.).However,those parameters were mainly predicted by using deterministic numerical weather prediction(NWP)models that include a wealth of uncertainties.The purpose of this study is to contribute in improving low-cost computationally ensemble forecasting of those parameters using analog ensemble method(AnEn)and comparing it to the operational mesoscale deterministic model(AROME)all over the main airports of Morocco using 5-yr period(2016-2020)of hourly datasets.An analog for a given station and forecast lead time is a past prediction,from the same model that has similar values for selected predictors of the current model forecast.Best analogs verifying observations form AnEn ensemble members.To picture seasonal dependency,two configurations were set;a basic configuration where analogs may come from any past date and a restricted configuration where analogs should belong to a day window around the target forecast.Furthermore,a new predictors weighting strategy is developed by using machine learning techniques(linear regression,random forest,and XGBoost).This approach is expected to accomplish both the selection of relevant predictors as well as finding their optimal weights,and hence preserve physical meaning and correlations of the used weather variables.Results analysis shows that the developed AnEn system exhibits a good statistical consistency and it significantly improves the deterministic forecast performance temporally and spatially by up to 50%for Bias(mean error)and 30%for RMSE(root-mean-square error)at most of the airports.This improvement varies as a function of lead times and seasons compared to the AROME model and to the basic AnEn configuration.The results show also that AnEn performance is geographically dependent where a slight worsening is found for some airports.