The SM2RAIN (soil moisture to rain) model has been widely used for rainfall estimation worldwide. However, due to the lack of sufficient ground observ…The SM2RAIN (soil moisture to rain) model has been widely used for rainfall estimation worldwide. However, due to the lack of sufficient ground observation, the SM2RAIN model driven by different passive microwave soil moisture products over the Tibetan Plateau has not been fully validated. In this article, four widely used satellite microwave soil moisture products (including SMAP, ASCAT, SMOS, and AMSR2) were used as input data for rainfall estimation. Rainfall data from eight ground observation stations during 2016–2018 were used to evaluate the overall performance of the SM2RAIN algorithm under various soil moisture products at different time aggregation scales. In addition, different satellite soil moisture products were merged to evaluate whether the combined soil moisture products could improve the performance of the SM2RAIN model. Finally, the rainfall estimates with different soil moisture data were further evaluated and compared with two benchmark rainfall products (IMERG and ERA5). Results indicate that: 1) Overall, SM2RAIN-SMAP has the highest rainfall estimation accuracy, but with the time aggregation scale up to 30 days, the mean R of the four rainfall estimates could reach above 0.8 and the mean value of Kling–Gupta efficiency could reach above 0.8. 2) Combined satellite soil moisture products can significantly improve the rainfall estimates. The SM2RAIN model performed the best when SMAP and ASCAT soil moisture products were combined. 3) Using the SMAP product or combined soil moisture products yielded more accurate rainfall estimates than the two benchmark rainfall products (IMERG and ERA5).more
The key factor that affects the inflow of radiant energy to the Earth's surface is the circulation of the atmosphere (caused by uneven distribution of…The key factor that affects the inflow of radiant energy to the Earth's surface is the circulation of the atmosphere (caused by uneven distribution of air pressure on the globe) and the related changes in the amount of aerosols and cloudiness. This paper identified the areas in the Euro-Atlantic region where the air pressure change had a significant impact on global solar radiation (GSR) changes over Poland, during the period 1986–2015. In general, growing GSR sums over Poland are to some extent related to the positive phase of the NAO (simultaneous pressure growth in the area of the Azores High and the pressure decrease in the area of the Icelandic Low). Correlation coefficient between the NAO index and GSR over Poland equals 0.18 (statistically significant at α = 0.05). In turn, in summer and autumn the pressure growth in southern Scandinavia results in a significant increase in the amount of GSR over Poland. Days with extremely large GSR sums (above the 95th percentile) are also prompted by the Azores High ridge which covers Central and Southern Europe, and by air mass inflow from the Atlantic.more
The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with impli…The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with implications in surface–atmosphere exchanges, climate variability, and global warming. Theoretical radiative transfer and observationally based studies identify the crucial role of clouds in modulating the temporal and spatial variability of DLR. In this study, a new machine learning algorithm that uses multivariate adaptive regression splines (MARS) and the combination of near-surface meteorological data with satellite cloud information is proposed. The new algorithm is compared with the current operational formulation used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Land Surface Analysis (LSA-SAF). Both algorithms use near-surface temperature and dewpoint temperature along with total column water vapor from the latest European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis ERA5 and satellite cloud information from the Meteosat Second Generation. The algorithms are trained and validated using both ECMWF-ERA5 and DLR acquired from 23 ground stations as part of the Baseline Surface Radiation Network (BSRN) and the Atmospheric Radiation Measurement (ARM) user facility. Results show that the MARS algorithm generally improves DLR estimation in comparison with other model estimates, particularly when trained with observations. When considering all the validation data, root mean square errors (RMSEs) of 18.76, 23.55, and 22.08 W·m−2 are obtained for MARS, operational LSA-SAF, and ERA5, respectively. The added value of using the satellite cloud information is accessed by comparing with estimates driven by ERA5 total cloud cover, showing an increase of 17% of the RMSE. The consistency of MARS estimate is also tested against an independent dataset of 52 ground stations (from FLUXNET2015), further supporting the good performance of the proposed model.more
Abstract
This paper analyzes the growing archive of 183-GHz water vapor absorption band measurements from the Advanced Microwave Sounding …Abstract
This paper analyzes the growing archive of 183-GHz water vapor absorption band measurements from the Advanced Microwave Sounding Unit B (AMSU-B) and Microwave Humidity Sounder (MHS) on board polar-orbiting satellites and document adjustments necessary to use the data for long-term climate monitoring. The water vapor channels located at 183.31 ± 1 GHz and 183.31 ± 3 GHz are sensitive to upper- and midtropospheric relative humidity and less prone to the clear-sky sampling bias than infrared measurements, making them a valuable but underutilized source of information on free-tropospheric water vapor. A method for the limb correction of the satellite viewing angle based upon a simplified model of radiative transfer is introduced to remove the scan angle dependence of the radiances. Biases due to the difference in local observation time between satellites and spurious trends associated with satellite orbital drift are then diagnosed and adjusted for using synthetic radiative simulations based on the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim). The adjusted, cloud-filtered, and limb-corrected brightness temperatures are then intercalibrated using zonal-mean brightness temperature differences. It is found that these correction procedures significantly improve consistency and quantitative agreement between microwave radiometric satellite observations that can be used to monitor upper- and midtropospheric water vapor. The resulting radiances are converted to estimates of the deep-layer-mean upper- and midtropospheric relative humidity, and can be used to evaluate trends in upper-tropospheric relative humidity from reanalysis datasets and coupled ocean–atmosphere models.more
This study pictures for the first time incoming solar radiation mean evolution in Central Africa, intercomparing 8 gridded products (namely CERES-EBAF…This study pictures for the first time incoming solar radiation mean evolution in Central Africa, intercomparing 8 gridded products (namely CERES-EBAF, CERES-SYN1deg, TPDC, CMSAF SARAH-2, CMSAF CLARA-A2, CAMS -JADE satellite products, as well as ERA5 reanalysis and WorldClim 2 interpolated measurements) and station -based estimations (FAOCLIM 2) or measurements. At the mean annual scale, all products picture low levels of global horizontal irradiance (GHI) to the west (SW Cameroon to SW Republic of Congo) and higher levels to-wards the north and south margins of the region. However, GHI levels in the CMSAF products are much higher than in CERES and TPDC. The mean annual cycles of GHI extracted for 6 sub-regions are bimodal, with two maxima during the two rainy seasons (March-May and September-November) and two minima during the two dry seasons (December-February and June-August). These seasonal cycles are well reproduced by most products except their amplitude which is dampened in TPDC. At the daily and sub-daily time-scales, products were compared with in-situ measurements from ten meteorological stations located in the western part of Central Africa. The products' performance is assessed through scores as bias and RMSE but also by considering the diurnal cycles' shape, amplitude and frequency of occurrence along the annual cycle. The products properly reproduce the shape of the four types of diurnal cycles with nonetheless noticeable differences in the cycle's frequencies of occurrence.more
We analyze a multi-model ensemble at a convection-resolving resolution based on the DYAMOND models and a resolution ensemble based on the limited-area…We analyze a multi-model ensemble at a convection-resolving resolution based on the DYAMOND models and a resolution ensemble based on the limited-area model COSMO over 40 days to study how tropical and subtropical marine low clouds are represented at a kilometer-scale resolution. The analyzed simulations produce low cloud fields that look in general realistic in comparison with satellite images. The evaluation of the radiative balance, however, reveals substantial inter-model differences and an under estimated low cloud cover in most models. Models that simulate increased low cloud cover are found to have a deeper marine boundary layer (MBL), stronger entrainment, and an enhanced latent heat flux. These findings demonstrate that some of the fundamental relations of the MBL are systematically represented by the model ensemble, which implies that the relevant dynamical processes start to become resolved on the model grid at a kilometer-scale resolution. A sensitivity experiment with the COSMO model suggests that differences in the strength of turbulent vertical mixing may contribute to the inter-model spread in cloud cover.more