Spatial and temporal monitoring of drought conditions using the satellite rainfall estimates and remote sensing optical and thermal measurements

Drought is an important natural disaster that causes devastating impacts on the ecosystem, livestock, environment, and society. So far, various remote-sensing methods have been developed to estimate drought conditions, each of which has advantages and restrictions. This study aims to monitor the real-time drought indices at the field scales via the integration of various earth observations. Our proposed method consists of two steps. In the first step, the relationships between long-term standardized precipitation indices (SPI) derived from PERSIANN-CDR rainfall data and two drought-dependent parameters derived from MODIS products, including normalized NDVI and soil-air temperature gradient, are obtained at the spatial resolution of PERSIANN-CDR grid (approximately 25 km). As the next step, the corresponding relationships are applied to estimate the drought index maps at the spatial resolution of MODIS products (1 km). Numerous analyses are carried out to evaluate the proposed method. The results revealed that, from various drought indices, including SPIs of different timescales (1, 3, 6, and 12-months), SPI-3 and SPI-6 are more appropriate to the proposed method in terms of correlation with temperature and vegetation parameters. The findings also demonstrate the competency of the proposed method in estimating SPI indices with average RMSE 0.67 and the average correlation coefficient of 0.74.     

Application of satellite observations to study the changes of hypoxic conditions in near-bottom water in the western part of Peter the Great Bay (the Sea of Japan)

In this paper we explore the possibilities of applying satellite ocean colour (OC) observations and SST to study the changes in the conditions of hypoxia in the near-bottom water in the western part of Peter the Great Bay. Near-bottom water hypoxia occurs in water bodies with increased organic matter influx when the dissolved oxygen (DO) consumed at its oxidation is not restored. Consumption of most DO is usually attributed to the oxidation of organic matter formed as a result of increased algae growth during water eutrophication. Satellite data on indicators of phytoplankton (chlorophyll-a concentration (Chl) and fluorescence (FLH)) allow to analyze the spatial-temporal changes of this substation. Coloured dissolved organic matter (CDOM), non-algal particles (NAP) influence on satellite Chl estimates and also on near-bottom water hypoxia formation. This study analyzes daily, seasonal, and inter-annual changes in the distributions of indicators (Chl, FLH, the coefficients of light absorption by coloured detrital matter (a_CDM) and light backscattering by suspended particles (b_bp)), based on the instant satellite OC data from MODIS-Aqua. Data on the Chl, the sea surface temperature (SST) from the MODIS-Aqua, the precipitation from the TRMM satellite and the hydrometeorological stations (HMSs), the wind speed and direction from HMS “Vladivostok” are used to study the influence of hydrometeorological conditions on the Chl values. These distributions were compared with the literary information based on field observations of the hypoxia cases in the same area and with the changes in the vertical DO, Chl, temperature, salinity distribution obtained by coastal expeditions in October-November 2010 and February-March 2011. Significant interrelations within 95% confidence level between the satellite Chl, FLH values calculated at the MUMM atmospheric correction and in situ Chl values obtained in the autumn of 2010 were reached separately for the cases with winds of northern and southern directions with the correlation coefficients of 0.71, 0.48 and 0.49, 0.71, respectively. Significant dependences of Chl on SST and Chl on wind speed explained by the influence of continental runoff and water ventilation were obtained. Therefore, the changes of Chl reflect the changes of hypoxic conditions in the near-bottom water. In Amursky Bay the onset of hypoxia was at the Chl and SST values equal to 4 mg m^?3 and 13 °C (↑ – at increasing SST); near Furugelm Island it was at 1.6 mg m^?3 and 25 °C (↑), 1 mg m^?3 and 21 °C (↓). The difference in the Chl values was reflected in the hypoxia onset timings that were the beginning of June (2011), August (2013), and September (2014), respectively. The water flow from the eastern coast of Amursky Bay in early August of 2013 recorded from the OC and SST satellite imagers appeared in an additional hypoxic zone. Decreased OC characteristics in the runoff of the Razdolnaya River in August-September of 2014 were a sign of hypoxia at its mouth. Near Furugelm Island the hypoxia destruction (increase in the DO level from 1 to 4.5 ml L^?1) was observed at the Chl of 0.9 mg m^?3 and SST = 18 °C (↓). At the autumn maximum of Chl equal to 1.7 mg m^?3 and SST = 4 °C (↓) in mid-November the DO level here increased to 8 ml L^?1. In Amursky Bay, short-term destructions/weakening of hypoxia manifested themselves in sharp increases of Chl. At that, the ratio between the Chl value and the approximation level was equal to 2 and higher for SST equal to 22–25 °C (↑), to 0.9 and higher for SST equal to 5–13 °C (↓). With the water stratification destruction in temperature and the noticeable weakening of the stratification in salinity (mid-November), the hypoxia destructed (the DO level increased from 2 to 6 ml L^?1). In this case, Chl and SST were about 3 mg m^?3 and 5 °C (↓).     

The impact of different background errors in the assimilation of satellite radiances and in-situ observational data using WRFDA for three rainfall events over Iran

Satellite radiances and in-situ observations are assimilated through Weather Research and Forecasting Data Assimilation (WRFDA) system into Advanced Research WRF (ARW) model over Iran and its neighboring area. Domain specific background error based on x and y components of wind speed (UV) control variables is calculated for WRFDA system and some sensitivity experiments are carried out to compare the impact of global background error and the domain specific background errors, both on the precipitation and 2-m temperature forecasts over Iran. Three precipitation events that occurred over the country during January, September and October 2014 are simulated in three different experiments and the results for precipitation and 2-m temperature are verified against the verifying surface observations. Results show that using domain specific background error improves 2-m temperature and 24-h accumulated precipitation forecasts consistently, while global background error may even degrade the forecasts compared to the experiments without data assimilation. The improvement in 2-m temperature is more evident during the first forecast hours and decreases significantly as the forecast length increases.