Assessment of past and future land use/cover change over Tordzie watershed in Ghana

Land use/ land cover (LULC) change has been identified as the main driving force of global change. The study investigated LULC change in Tordzie watershed in Ghana and predicted the future development. The supervised classification procedure was applied to Landsat images of 1987, 2003, and 2017. The cellular automata–Markov model embedded in IDRISI 17 software was employed to model LULC for the years 2030 and 2050. The trend of LULC change was exploited from 1987 to 2003, from 2003 to 2017, and projected to 2030 and 2050. Settlement and crop land, respectively, increased from 2.68% to 16.46% in 1987 to 3.65% and 53.47% in 2003 and finally to 20.61% and 58.52% in 2017. Vegetation cover declined from 23.2% in 1987 to 13.9% in 2003 and finally to 11.3% in 2017. The annual rate of change was determined. In 2030 and 2050, the dominant land use type will be crop land (56%). However, it decreased between 2017 and 2030 by −1.73%. The findings of the study are very relevant to land and water resource planners, policy formulators and implementers, and environmental and climate change advocates. Sustainable land use policy and its implementation are recommended

Stratosphärische O3-, NO2- und NO3-Konzentrationsprofile aus spektroskopischen Mondokkultationsmessungen von SCIAMACHY: Retrieval, Validation und Interpretation

Stratospheric profiles of O3, NO2, and NO3 were retrieved from lunar transmitted spectra measured by SCIAMACHY over high southern latitude (60Ã °S - 90Ã °S), from March to June 2003 and January to June 2004. The global spectral fitting method by the differential optical depth approach was applied to simultaneously fit O3 and NO2 using the spectral range of 430-460 nm and 510-560 nm. Furthermore, NO3 was fitted using the visible spectral range of 615-680 nm containing NO3 intense absorption bands at 623 nm and 662 nm. Validation of the retrieved SCIAMACHY O3 and NO2 profiles were carried out. O3 profiles were compared with HALOE,POAM-III, SAGE-II and -III, and MIPAS. Whereas NO2 profiles were compared with HALOE, MIPAS, and SAGE-III. The validation results show that the quality of SCIAMACHY O3profiles is high, within 10-25% and 10-35% for O3 and NO2 respectively. To test our current understanding of NO3 chemistry, the retrieved NO3 vertical profiles were compared with a full photochemical model and a relatively simple steady state model. The calculations from a full photochemical model constrained by retrieved O3 and analyzed ECMWF temperatures in the altitude range between 24 to 45 km. Below about 35-40 km, observed NO3 is well reproduced by photochemical steady state calculations. Differences between observed and modeled NO3 are within the estimated accuracy of 20-35%, demonstrating that we have a reasonable understanding of the behavior of NO3 in the polar stratosphere

Stratospheric O3, NO2, and NO3 number density profile from SCIAMACHY lunar occultation spectroscopic measurements: Retrieval, validation and interpretation

Stratospheric profiles of O3, NO2, and NO3 were retrieved from lunar transmitted spectra measured by SCIAMACHY over high southern latitude (60à °S - 90à °S), from March to June 2003 and January to June 2004. The global spectral fitting method by the differential optical depth approach was applied to simultaneously fit O3 and NO2 using the spectral range of 430-460 nm and 510-560 nm. Furthermore, NO3 was fitted using the visible spectral range of 615-680 nm containing NO3 intense absorption bands at 623 nm and 662 nm. Validation of the retrieved SCIAMACHY O3 and NO2 profiles were carried out. O3 profiles were compared with HALOE,POAM-III, SAGE-II and -III, and MIPAS. Whereas NO2 profiles were compared with HALOE, MIPAS, and SAGE-III. The validation results show that the quality of SCIAMACHY O3profiles is high, within 10-25% and 10-35% for O3 and NO2 respectively. To test our current understanding of NO3 chemistry, the retrieved NO3 vertical profiles were compared with a full photochemical model and a relatively simple steady state model. The calculations from a full photochemical model constrained by retrieved O3 and analyzed ECMWF temperatures in the altitude range between 24 to 45 km. Below about 35-40 km, observed NO3 is well reproduced by photochemical steady state calculations. Differences between observed and modeled NO3 are within the estimated accuracy of 20-35%, demonstrating that we have a reasonable understanding of the behavior of NO3 in the polar stratosphere

Optimal Temporal Filtering of the Cosmic-Ray Neutron Signal to Reduce Soil Moisture Uncertainty

Cosmic ray neutron sensors (CRNS) are increasingly used to determine field-scale soil moisture (SM). Uncertainty of the CRNS-derived soil moisture strongly depends on the CRNS count rate subject to Poisson distribution. State-of-the-art CRNS signal processing averages neutron counts over many hours, thereby accounting for soil moisture temporal dynamics at the daily but not sub-daily time scale. This study demonstrates CRNS signal processing methods to improve the temporal accuracy of the signal in order to observe sub-daily changes in soil moisture and improve the signal-to-noise ratio overall. In particular, this study investigates the effectiveness of the Moving Average (MA), Median filter (MF), Savitzky–Golay (SG) filter, and Kalman filter (KF) to reduce neutron count error while ensuring that the temporal SM dynamics are as good as possible. The study uses synthetic data from four stations for measuring forest ecosystem–atmosphere relations in Africa (Gorigo) and Europe (SMEAR II (Station for Measuring Forest Ecosystem–Atmosphere Relations), Rollesbroich, and Conde) with different soil properties, land cover and climate. The results showed that smaller window sizes (12 h) for MA, MF and SG captured sharp changes closely. Longer window sizes were more beneficial in the case of moderate soil moisture variations during long time periods. For MA, MF and SG, optimal window sizes were identified and varied by count rate and climate, i.e., estimated temporal soil moisture dynamics by providing a compromise between monitoring sharp changes and reducing the effects of outliers. The optimal window for these filters and the Kalman filter always outperformed the standard procedure of simple 24-h averaging. The Kalman filter showed its highest robustness in uncertainty reduction at three different locations, and it maintained relevant sharp changes in the neutron counts without the need to identify the optimal window size. Importantly, standard corrections of CRNS before filtering improved soil moisture accuracy for all filters. We anticipate the improved signal-to-noise ratio to benefit CRNS applications such as detection of rain events at sub-daily resolution, provision of SM at the exact time of a satellite overpass, and irrigation applications

Bias correction and spatial disaggregation of satellite-based data for the detection of rainfall seasonality indices

Like many other African countries, Ghana's rain gauge networks are rapidly deteriorating, making it challenging to obtain real-time rainfall estimates. In recent years, significant progress has been made in the development and availability of real-time satellite precipitation products (SPPs). SPPs may complement or substitute gauge data, enabling better real-time forecasting of stream flows, among other things. However, SPPs still have significant biases that must be corrected before the rainfall estimates can be used for any hydrologic application, such as real-time or seasonal forecasting. The daily satellite-based rainfall estimate (CHIRPS-v2) data were bias-corrected using the Bias Correction and Spatial Disaggregation (BSCD) approach. The study further investigated how bias correction of daily satellite-based rainfall estimates affects the identification of seasonality and extreme rainfall indices in Ghana. The results revealed that the seasonal and annual rainfall patterns in the region were better represented after the bias correction of the CHIRPS-v2 data. We observed that, before bias correction, the cessation dates in the country's southwest and upper middle regions were slightly different. However, they matched those of the gauge well after bias correction. The novelty of this study is that, in addition to improving rainfall using CHIRPS data, it also enhances the identification of seasonality indices. The paper suggests the BCSD approach for correcting rainfall estimates from other algorithms using long-term historical records indicative of the rainfall variability area under consideration

A meteorological dataset of the West African monsoon during the 2016 DACCIWA campaign

International audienceAbstractAs part of the Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) project, extensive in-situ measurements of the southern West African atmospheric boundary layer (ABL) have been performed at three supersites Kumasi (Ghana), Savè (Benin) and Ile-Ife (Nigeria) during the 2016 monsoon period (June and July). The measurements were designed to provide data for advancing our understanding of the relevant processes governing the formation, persistence and dissolution of nocturnal low-level stratus clouds and their influence on the daytime ABL in southern West Africa. An extensive low-level cloud deck often forms during the night and persists long into the following day strongly influencing the ABL diurnal cycle. Although the clouds are of a high significance for the regional climate, the dearth of observations in this region has hindered process understanding. Here, an overview of the measurements ranging from near-surface observations, cloud characteristics, aerosol and precipitation to the dynamics and thermodynamics in the ABL and above, and data processing is given. So-far achieved scientific findings, based on the dataset analyses, are briefly overviewed.</jats:p