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Potentially, the greatest benefit of commercial microwave links (CMLs) as opportunistic rainfall sensors lies in regions that lack dedicated rainfall sensors, most notably low- and middle-income countries. However, current CML rainfall retrieval algorithms are predominantly tuned and applied to (European) CML networks in temperate or Mediterranean climates. This study investigates whether local quantitative precipitation estimates from CMLs in a tropical region, specifically Sri Lanka, can be improved by optimizing two dominant parameters in the rainfall retrieval algorithm RAINLINK, namely, the wet antenna attenuation correction factor Aa and the relative contribution of minimum and maximum received signal levels α. Using a grid search, based on 10 months of CML data from 22 link–gauge clusters consisting of 105 sublinks that lie within 1 km of a daily rain gauge, the optimal values of Aa and α are first derived for the entire country and compared to the default RAINLINK values. Subsequently, the CMLs are grouped by link length, frequency, climate zone, and daily rainfall depth classes, and Aa and α are derived for each of these classes. Calibrating parameters on all clusters across the country only leads to minor improvements. The actual optimal Aa and α values depend on the performance metric favored. Calibrating on network properties, particularly short link length and high-frequency classes, does significantly improve rainfall estimates. By relating the optimal Aa and α values to known network metadata, the results from this study are potentially applicable to other tropical CML networks that lack nearby reference rainfall data. Significance Statement: The purpose of this study is to improve rainfall estimates from commercial microwave links in Sri Lanka by optimizing two important rainfall retrieval algorithm parameters. Our results show that relating the optimal parameter values to operating frequency and pathlength improves rainfall estimates more than applying a single optimal parameter set to the entire network. By relating the optimal parameter values to readily known network properties, we aim to make these results applicable to other tropical countries, particularly low- and middle-income countries, that lack adequate reference rainfall data to calibrate rainfall estimates from commercial microwave links on. [ABSTRACT FROM AUTHOR]

The miombo woodland is the largest dry woodland formation in sub-Saharan Africa, covering an estimated area of 2.7–3.6 million km 2. Compared to other global ecosystems, the miombo woodland demonstrates unique interactions between plant phenology and climate. For instance, it experiences an increase in the leaf area index (LAI) during the dry season. However, due to limited surface exchange observations in the miombo region, there is a lack of information regarding the effect of these properties on miombo woodland evaporation. It is crucial to have a better understanding of miombo evaporation for accurate hydrological and climate modelling in this region. Currently, the only available regional evaporation estimates are based on satellite data. However, the accuracy of these estimates is questionable due to the scarcity of field estimates with which to compare. Therefore, this study aims to compare the temporal dynamics and magnitudes of six satellite-based evaporation estimates – the Topography-driven Flux Exchange (FLEX-Topo) model, Global Land Evaporation Amsterdam Model (GLEAM), Moderate-Resolution Imaging Spectrometer (MODIS) MOD16 product, operational Simplified Surface Energy Balance (SSEBop) model, Thornthwaite–Mather climatic Water Balance (TerraClimate) dataset, and Water Productivity through Open access of Remotely sensed derived data (WaPOR) – during different phenophases in the miombo woodland of the Luangwa Basin, a representative river basin in southern Africa. The goal of this comparison is to determine if the temporal dynamics and magnitudes of the satellite-based evaporation estimates align with the documented feedback between miombo woodland and climate. In the absence of basin-scale field observations, actual evaporation estimates based on the multi-annual water balance (Ewb) are used for comparison. The results show significant discrepancies among the satellite-based evaporation estimates during the dormant and green-up and mid-green-up phenophases. These phenophases involve substantial changes in miombo species' canopy phenology, including the co-occurrence of leaf fall and leaf flush, as well as access to deeper moisture stocks to support leaf flush in preparation for the rainy season. The satellite-based evaporation estimates show the highest agreement during the senescence phenophase, which corresponds to the period of high temperature, high soil moisture, high leaf chlorophyll content, and highest LAI (i.e. late rainy season into the cool-dry season). In comparison to basin-scale actual evaporation, all six satellite-based evaporation estimates appear to underestimate evaporation. Satellite-based evaporation estimates do not accurately represent evaporation in this data-sparse region, which has a phenology and seasonality that significantly differ from the typical case in data-rich ground-truth locations. This may also be true for other locations with limited data coverage. Based on this study, it is crucial to conduct field-based observations of evaporation during different miombo species phenophases to improve satellite-based evaporation estimates in miombo woodlands. [ABSTRACT FROM AUTHOR]

Terrestrial microwave links are increasingly being used to estimate path-averaged precipitation by determining the attenuation caused by rainfall along the link path, mostly with commercial microwave links from cellular telecommunication networks. However, the temporal resolution of these rainfall estimates and the method to derive them are often determined by the temporal sampling strategy that is employed by the mobile network operators. Currently, the links are most often sampled at a temporal resolution of 15 min with a recording of the minimum and maximum values, while more recently, a form of instantaneous sampling with possible intervals up to 1 s has also been set up. For rainfall research purposes, often high temporal resolutions in combination with averaged values are preferred. However, it is uncertain how these various temporal sampling strategies affect the estimated rainfall intensity. Here we aim to understand how temporal sampling strategies affect the measured rainfall intensities using microwave links. To do so, we use data from three collocated microwave links, two 38 GHz and one 26 GHz, sampled at 20 Hz and covering a 2.2 km path over the city of Wageningen, the Netherlands. We aggregate the microwave link power levels to multiple time intervals (1 s to 60 min) and use a mean, instantaneous, and minimum and maximum value to characterize the signal. Based on the aggregated data, we compute rainfall intensities and compare these with 20 Hz rainfall estimates, such that we isolate errors and uncertainties caused by the sampling strategies from instrumental effects, such as different biases between instruments and representativeness errors. In general, our results show that for all sampling strategies, an increase in sampling time interval reduces the performance of the rainfall estimates, which especially holds for the instantaneous sampling strategy. Even the mean sampling strategy, which generally performs best of all strategies, is sensitive to this reduction in temporal resolution and could lead to significant underestimations. This sensitivity of the mean sampling to the temporal resolution seems to be largely affected by the non-linear relation between attenuation and rainfall. The min–max sampling strategy is mostly prone to minor underestimations or large overestimations of the path-averaged rainfall intensities. Moreover, our results, including a comparison with theoretical events, show that the attenuation due to wet antennas not only affects the comparison between the rainfall estimates obtained with a microwave link and another reference instrument but also has a significant influence on the performance of the rainfall retrieval algorithm, especially for devices with relatively long duration of the wet-antenna attenuation combined with the longer sampling time intervals. Overall, this study demonstrates the effect a selected sampling strategy can have on rainfall intensity estimates using (commercial) microwave links. [ABSTRACT FROM AUTHOR]

Quantification of precipitation partitioning into evaporation and runoff is crucial for predicting future water availability. Within the widely used Budyko Framework, which relates the long-term aridity index to the long-term evaporative index, curvilinear relationships between these indices (i.e., parametric Budyko curves) allow for the quantification of precipitation partitioning under prevailing climatic conditions. A movement along a Budyko curve with changes in the climatic conditions has been used as a predictor for catchment behaviour under change. However, various studies have reported deviations around these curves, which raises questions about the usefulness of the method for future predictions. To investigate whether parametric Budyko curves still have predictive power, we quantified the global, regional, and local evolution of deviations of catchments from their parametric Budyko curves over multiple subsequent 20-year periods throughout the last century, based on historical long-term water balance data from over 2000 river catchments worldwide. This process resulted in up to four 20-year distributions of annual deviations from the long-term mean parametric curve for each catchment. To use these distributions of deviations to predict future deviations, the temporal stability of these four distributions of deviations was evaluated between subsequent periods of time. On average, it was found that the majority of 62 % of study catchments did not significantly deviate from their expected parametric Budyko curves. From the remaining 38 % of catchments that deviated from their expected curves, the long-term magnitude of median deviations remains minor, with 70 % of catchments falling within the range of ±0.025 of the expected evaporative index. Furthermore, a significant majority of catchments, constituting around the same percentage, were found to have stable distributions of deviations across multiple time periods, making them well-suited to statistically predict future deviations with high predictive power. These findings suggest that while trajectories of change in catchments do not strictly follow the expected long-term mean parametric Budyko curves, the deviations are minor and quantifiable. Consequently, taking into account these deviations, the parametric formulations of the Budyko Framework remain a valuable tool for predicting future evaporation and runoff under changing climatic conditions, within quantifiable margins of error. [ABSTRACT FROM AUTHOR]

Storage change in heat in the soil is one of the main components of the energy balance and is essential in studying the land–atmosphere heat exchange. However, its measurement proves to be difficult due to (vertical) soil heterogeneity and sensors easily disturbing the soil. Improvements in the precision and resolution of distributed temperature sensing (DTS) equipment has resulted in its widespread use in geoscientific studies. Multiple studies have shown the added value of spatially distributed measurements of soil temperature and soil heat flux. However, due to the spatial resolution of DTS measurements (∼30 cm), soil temperature measurements with DTS have generally been restricted to (horizontal) spatially distributed measurements. This paper presents a device which allows high-resolution measurements of (vertical) soil temperature profiles by making use of a 3D-printed screw-like structure. A 50 cm tall probe is created from segments manufactured with fused-filament 3D printing and has a helical groove to guide and protect a fiber-optic (FO) cable. This configuration increases the effective DTS measurement resolution and will inhibit preferential flow along the probe. The probe was tested in the field, where the results were in agreement with the reference sensors. The high vertical resolution of the DTS-measured soil temperature allowed determination of the thermal diffusivity of the soil at a resolution of 2.5 cm, many times better than what is feasible using discrete probes. A future improvement in the design could be the use of integrated reference temperature probes, which would remove the need for DTS calibration baths. This could, in turn, support making the probes "plug and play" into the shelf instruments without the need to splice cables or experience in DTS setup design. The design can also support the integration of an electrical conductor into the probe and allow heat tracer experiments to derive both the heat capacity and the thermal conductivity over depth at high resolution. [ABSTRACT FROM AUTHOR]

Storage of heat in the soil is one of the main components of the energy balance, and is essential in studying the land- atmosphere heat exchange. However, its measurement proves to be difficult, due to (vertical) soil heterogeneity and sensors easily disturbing the soil. Improvements in precision and resolution of Distributed Temperature Sensing (DTS) equipment has resulted in widespread use in geoscientific studies. Multiple studies have shown the added value of spatially distributed measurements of soil temperature and soil heat flux. However, due to the spatial resolution of DTS measurements (~30 cm), soil temperature measurements with DTS have generally been restricted to (horizontal) spatially distributed measurements. In this paper a device is presented which allows high resolution measurements of (vertical) soil temperature profiles, by making use of a 3D printed screw-like structure. A 50 cm tall probe is created from segments manufactured with fused filament 3D printing, and has a helical groove to guide and protect a fiber optic cable. This configuration increases the effective DTS measurement resolution, and will inhibit preferential flow along the probe. The probe was tested in the field, where the results were in agreement with the reference sensors. The high vertical resolution of the DTS-measured soil temperature allowed determination of the thermal diffusivity of the soil at a resolution of 2.5 cm, many times better than feasible with discrete probes. Future improvements in the design could be integrated reference temperature probes, which would remove the need for DTS calibration baths. This could, in turn, support making the probes 'plug and play' of the shelf instruments, without the need to splice cables or experience in DTS-setup design. The design can also support integrating an electrical conductor into the probe, and allow heat tracer experiments to derive both the heat capacity and thermal conductivity over depth at high resolution. [ABSTRACT FROM AUTHOR]

Terrestrial microwave links are increasingly being used to estimate path-averaged precipitation by determining the attenuation caused by rainfall along the link path, mostly with commercial microwave links from cellular telecommunication networks. However, the temporal resolution of and method to derive these rainfall estimates is often determined by the temporal sampling strategy that is employed by the mobile network operators. Currently, the links are most often sampled at a temporal resolution of 15 minutes with a recording of the minimum and maximum values, while more recently also a form of instantaneous sampling with possible intervals up to 1 s has been set up. For rainfall research purposes, often high temporal resolutions in combination with averaged values are preferred. However, it is uncertain how these various temporal sampling strategies affect the estimated rainfall intensity. Here we aim to understand how temporal sampling strategies affect the measured rainfall intensities using microwave links. To do so, we use data from three collocated microwave links, two 38 GHz and one 26 GHz, sampled at 20 Hz and covering a 2.2 km path over the city of Wageningen, the Netherlands. We aggregate the microwave link power levels to multiple time intervals (1 s to 60 min) and use a mean, instantaneous, and minimum and maximum value to characterize the signal. Based on the aggregated data, we compute rainfall intensities and compare these with 20 Hz rainfall estimates, such that we isolate errors and uncertainties caused by the sampling strategies from instrumental effects, such as different biases between instruments and representativeness errors. In general, our results show that for all sampling strategies an increase in sampling time interval reduces the performance of the rainfall estimates, which especially holds for the instantaneous sampling strategy. Even the mean sampling strategy, which generally performs best of all strategies, is sensitive to this reduction in temporal resolution and could lead to significant underestimations. In this, the non-linear relation between attenuation and rainfall intensity seems to play an important role. The min-max sampling strategy is mostly prone to minor underestimations or large overestimations of the path-averaged rainfall intensities. Moreover, our results, including a comparison with theoretical events, show that the attenuation due to wet antennas not only affects the comparison between the rainfall estimates obtained with a microwave link and another reference instrument, but also has a significant influence on the rainfall retrieval algorithm. Overall, this study demonstrates the effect a selected sampling strategy can have on rainfall intensity estimates using (commercial) microwave links. [ABSTRACT FROM AUTHOR]

Stormwater is a vital resource and dynamic driver of terrestrial ecosystem processes. However, processes controlling interactions during and shortly after storms are often poorly seen and poorly sensed when direct observations are substituted with technological ones. We discuss how human observations complement technological ones and the benefits of scientists spending more time in the storm. Human observation can reveal ephemeral storm-related phenomena such as biogeochemical hot moments, organismal responses, and sedimentary processes that can then be explored in greater resolution using sensors and virtual experiments. Storm-related phenomena trigger lasting, oversized impacts on hydrologic and biogeochemical processes, organismal traits or functions, and ecosystem services at all scales. We provide examples of phenomena in forests, across disciplines and scales, that have been overlooked in past research to inspire mindful, holistic observation of ecosystems during storms. We conclude that technological observations alone are insufficient to trace the process complexity and unpredictability of fleeting biogeochemical or ecological events without the shower thoughts produced by scientists' human sensory and cognitive systems during storms. [ABSTRACT FROM AUTHOR]

Complex African ecosystems such as the Miombo Woodland, with unique plant phenology, have evaporation dynamics that have not been investigated due to very few, if at all existant, flux tower observations. Furthermore, significant differences have been observed in satellite-based evaporation estimates in the Miombo Woodland especially in the dry season. Therefore, deciding which sattelite evaporation product to use in this ecosystem is difficult, as these products vary in many respects. In this study, the actual evaporation estimates for six satellite-based evaporation estimates are compared across Miombo Woodland phenophases in the Luangwa Basin, in southern Africa. In the absence of basin scale field observations, the actual evaporation estimated using the general water balance is used as reference, to which the six satellite-based evaporation estimates have been compared. Our results show significant variation in actual evaporation estimates in the water limited, high temperature and lower forest canopy cover and leaf chlorophyll conditions in the dormant phenophase. Lowest variation is observed in water abundant, high temperature, high leaf chlorophyll content and high forest canopy cover in the maturity/peak phenophase(s). Compared to the basin scale water balance actual evaporation, all six satellite-based evaporation estimates appear to underestimate evaporation. The results of underestimation at basin scale agrees with local field observations in a dense Miombo Woodland in the Luangwa Basin, which indicates that satellite-based evaporation estimates generally underestimate dry season (dormant phenophase) and early rain season (green-up phenophase) actual evaporation. The discrepancies in dry season satellite-based evaporation estimates may be cuased by the Miombo Woodland species' phenological adaptation attributes such as: leaf fall, leaf flush, access to deep soil moisture and the within vegetation water storage, coupled with heterogenous plant species response to phenological stimuli. Therefore, it appears that satellite-based evaporation estimates using model structure, processes and inputs that are capable of capturing Miombo species dry season phenological interaction with climate are likely to have actual evaporation estimates closer to field conditions. [ABSTRACT FROM AUTHOR]

Atmospheric water demand drives forest evaporation controlled by the plant physiological properties within available moisture storage thresholds. The pattern and magnitude of African Miombo Forest transpiration across dry season canopy phenophases are unknown. This is because estimating forest evaporation in African ecosystems continues to be a challenge as flux observation towers are scant, if not completely lacking in most ecosystems like the Miombo Forest, one of Africa’s largest woodland formations. Moreover, in the Miombo Forest, satellite data-based evaporation products (i.e., GLEAM, MOD16, SSEBop and WaPOR) show significant discrepancies in both pattern and amounts of evaporation especially during the dry season canopy phenophases. Despite the main limitations with estimation of forest evaporation the development and application of the distributed temperature sensing (DTS) system is providing deepened insights and improved accuracy in forest energy partitioning for evaporation assessment. In this study the Bowen ratio distributed temperature sensing (BR-DTS) approach is used to partition available energy and estimate evaporation across three Miombo Forest canopy phenophases covering the entire 2021 dry season and early rain season. Furthermore, four satellite evaporation products are compared to the field observations. Results show that evaporation appears to follow the net radiation and air temperature pattern with the lowest values observed during the most net radiation and air temperature depressed periods and highest values during the peak net radiation and air temperature. Evaporation continues to rise even during the driest period in the dormant leaf phenophase when canopy cover is said to be at its minimum. This is possibly facilitated by the retention of about 70 percent canopy cover during the dry season which transpires within the adapted thresholds constrained by physiological properties of each Miombo Forest species with access to ground water and vegetative water storage. This goes to show that during the dry season Miombo species may not be as water stressed as imagined. When compared to field observations all four-satellite evaporation products underestimate evaporation with only the WaPOR showing a similar pattern of evaporation during the dry season. The differences between field observations and satellite-based evaporation products can be attributed to the model structure, processes as well as inputs. [ABSTRACT FROM AUTHOR]