‘Every Earthquake a Precursor According to Scale’ (EEPAS) is a model to forecast earthquakes within the coming months, years and decades, depending on magnitude. EEPAS performs well for seismically active regions including New Zealand (NZ) and has been formally evaluated in Collaboratory for the Study of Earthquake Predictability (CSEP) centres in NZ and California, USA. It has been used for practical forecasting in NZ for nearly a decade. An EEPAS forecast is formed by accumulating the contributions from past earthquakes to the expectation of future earthquakes. It uses the precursory scale increase (Ψ) phenomenon along with three predictive spatial, temporal and magnitude scaling relations. For a particular mainshock, Ψ is identified as a prior sharp increase in the occurrence of minor earthquakes. Each identification is represented by a value of precursor magnitude MP, precursor time TP and precursory area AP. An algorithm to automatically identify Ψ was developed and applied to real and synthetic earthquake catalogs. Multiple identifications of Ψ were obtained for most mainshocks. A trade-off between AP and TP was observed among such multiple identifications. Here, we examine the implications of the trade-off for the EEPAS temporal and spatial scaling parameters aT and σA. The EEPAS parameters were initially fitted to the NZ earthquake catalog from 1986-2006. The EEPAS parameters are now refitted with a sequence of fixed values for aT and then for σA. The range of fixed values constrain the respective temporal and spatial scales to vary by a factor of a hundred. Results confirm the existence of a similar space-time trade-off in EEPAS as in Ψ, with large aT values being associated with small σA values and vice versa. We conclude that the space-time trade-off is an intrinsic feature of precursory seismicity. This exists independently of other influences, such as the local strain rate, that may contribute to scatter in the predictive scaling relations. Mixing EEPAS models with parameters along the trade-off line should improve forecasting.

The east coast of India is prone to tropical cyclones. During pre-monsoon and post-monsoon seasons, almost every year, cyclones are developed over the Bay of Bengal and Andaman Sea. On 20 May 2020, tropical cyclone Amphan made initial landfall at Bakkhali in the West Bengal, India at 2:30 PM (local time) with wind velocity more than 175 km/h, which further intensified and moved into adjoining Bangladesh coastal areas on 21 May 2020 with highest wind speed 260 km/h. The cyclone formed on 16 May 2020 and dissipated finally on 21 May 2020. More than 22,000 houses in Coastal parts of West Bengal, and nearly 220,000 houses in Bangladesh coastal areas were damaged, and approximately 4.2 millions of people in both the countries were relocated to safe places. This cyclone affected many of the eastern states of India and 9 coastal districts of Bangladesh due to heavy rainfall that caused deadly flood. In West Bengal, Kolkata airport was flooded, and all the flights were closed. We have carried out analysis of meteorological and atmospheric parameters that helped in formation of the cyclone. Detailed analysis of multi satellite sensors, ground and Argo data have been carried out that show pronounced changes in ecological, atmospheric and ocean color parameters. The ocean parameters such as chlorophyll concentration, dissolved oxygen, salinity, sea surface and sub-surface temperature show strong changes in ocean ecology that have serious impacts on the marine life. Strong stratospheric-tropospheric exchange caused the rise in various trace gases close to the ground. A detailed damage analysis along the Eastern part of India and Bangladesh coast and major nearby cities and migration of the population from the affected region will be discussed.

Although mass and energy in Jupiter's magnetosphere mostly come from the innermost Galilean moon Io's volcanic activity, solar wind perturbations can play crucial roles in releasing the magnetospheric energy and powering aurorae in Jupiter's polar regions. The relative importance of solar wind and internal processes in driving Jupiter's auroras remains poorly understood. Recently, the contemporaneous measurements from NASA Juno mission and the Hubble Space Telescope provide an unprecedented opportunity to determine the magnetospheric drivers of auroral variations at Jupiter, and key evidence on how solar wind would affect the auroral brightening. In this presentation, we will discuss several important advances on several distinctive auroral morphologies at Jupiter, i.e., auroral dawn storm, the main auroral brightening and auroral injection processes. We find that magnetic reconnection and dipolarization play crucial roles in driving these auroras, and the auroral drivers for the Earth and Jupiter have more in common than ever expected.

Field reversals are some of the most prominent and commonly known temporal variations of the geomagnetic field. Polarity changes have been observed in seafloor magnetisation patterns, volcanic records, sediment sequences, speleothem records, and have been reported in geodynamo simulations. However, open questions remain concerning the phenomenology and underlying causes of this process. In particular, there is currently no consensus about the temporal scales over which geomagnetic reversals occur. Numerical simulations aimed at understanding Earth’s million-year evolution have predicted a time scale on the order of thousands of years. On the other hand, analysis of a lacustrine sequence in the central Italian Apennines suggests that the most recent geomagnetic reversal (the Matuyama-Brunhes) took place in as short as 13 years, requiring VGP latitudinal changes of the order of 10 degrees/yr [Sagnotti, L. et al. (2015). GJI, 204(2), 798-812]. This extremely short decadal time scale challenges our current understanding of the geodynamo and present-day numerical models. Here we derive fluid flows at the top of Earth’s outer core that optimise either the rate of dipole decay or directional changes local to the Italian Apennines, subject to a minimal number of physical ingredients. Specifically, we neglect the internal dynamics and prescribe a total flow kinetic energy that is consistent with observational bounds. Our optimal flows can drive an instantaneous VGP latitudinal change of at most 5 degrees/yr during the Matuyama-Brunhes transition. Extending the methodology to account for the spatio-temporal evolution of the magnetic field, we find that this solution does not drive a global reversal, but only changes that are highly localised around the Mediterranean and West-African regions. Solutions that optimise the rate of dipole decay suggest that full reversal would take at least 380 years.

The urban environment directly influences the evolution of the Urban Boundary Layer (UBL). Heat adaptation strategies proposed to help cities respond to global change and urban induced warming, are also expected to reduce the intensity of convective mixing and decrease UBL depth, thereby reducing the volume of air available to pollutant dilution and dispersion. We use 20 km resolution WRF-ARW decadal scale simulations that account for end of 21st century greenhouse gas emissions, urban expansion and intensive and uniform implementation of cool roofs, green roofs and street trees to investigate the individual and combined impacts of these drivers on the dynamics of the UBL over the Conterminous US (CONUS). Results indicate that combined impacts of climate change and urban expansion are expected to increase summer (JJA) daytime UBL depth in the eastern regions of CONUS (peak value: Δh ≅ 80 m over Atlanta metro area). When adaptation strategies are applied, summer daytime UBL depth is reduced by a few hundred meters (peak value: Δh ≅ -310 m over Dallas and Fort Worth metro areas) in all CONUS regions as a consequence of decreased surface sensible heat fluxes. Adaptation impacts are greater inland and smaller over coastal cities. In arid regions, the adaptation induced increase in latent heat fluxes can counterbalance the projected decrease in UBL depth. Furthermore, adaptation strategies are expected to increase the static stability of both daytime and nighttime UBLs and decrease the magnitude of vertical winds, inducing earlier and stronger subsidence (peak value: Δm/s ≅ -0.05 m over Phoenix and Tucson metro areas). In light of these findings, ongoing work addressing these aspects with convection resolving, high-resolution simulations is needed to determine whether the widespread implementation of urban adaptation measures could have deleterious effects for urban air quality in the cities of the future Contiguous US.

Eutrophication-induced hypoxia in a coastal estuarine system results in the deterioration of water quality, which is a growing issue worldwide. In early August 2016, an anoxic event caused the mortality of up to 75 percent of cultured oysters in aquaculture leases of northern Tracadie Bay, New Brunswick (TNB). Field observations revealed that, although the occurrence of summer hypoxia in north TNB is linked with anthropogenic stressors, changes in the geomorphology of one of the bay’s inlet are likely to play a significant role in escalating the eutrophic conditions. However, adequate information on the circulation dynamics of TNB estuarine system was lacking. To address this knowledge gap, a high-resolution spatially-explicit hydrodynamic model was developed for TNB to evaluate the possible physical processes involved in generation of hypoxia leading to oyster mortality. The model showed high skill (0.93) in south TNB in simulating water level elevations and slightly lower skill (0.85) in north TNB. Findings from modeling scenarios based on past, present and future inlet geomorphology suggest that it has strong consequences on intricate circulation patterns, renewal of water and transport. Further, the model is coupled with a volume advection-dispersion tracer module to track the dissemination of effluent and identify areas at risk of hypoxia. Residual flow estimates revealed poorly-circulated stagnant areas, consistent with hot spots in sediment organic matter content. Outcomes from this study will be of relevance for the management of water quality and aquaculture practices.

As wildfires become more prevalent and destructive, it is imperative to understand the impacts they have on the watersheds they burn. One particularly understudied aspect of wildfire-associated water quality impairment is the generation of polycyclic aromatic hydrocarbons (PAHs), a class of organic contaminants with carcinogenic, mutagenic, and ecotoxic properties. As a case study, we investigate PAH impacts associated with the 2018 Woolsey Fire, which burned over half of the Malibu Creek Watershed near Los Angeles, California. We collected soil and water samples periodically and during rain events over three years following the fire. Sampling sites were distributed through the watershed to incorporate samples from all major tributaries of Malibu Creek and to capture varying topography, geology, land use, and fire intensity. We found PAH concentrations exceeding EPA Ambient Water Quality Criteria, primarily during rain events, through the second wet season after the fire. Using molecular ratio approaches, the PAHs detected in water samples were directly linked to burned soil. Elevated PAH concentrations were associated with suspended particulate matter, which was in turn directly related to stream discharge and precipitation intensity. However, significant geographic variability was observed during the second wet season, suggesting topography, burn intensity, and other factors play a role in post-fire recovery and the persistence of fire-derived PAHs in the watershed. We investigated the contribution of these factors through a combination of long-term soil and water sampling, assessment of suspended particulate material, analysis of the variation and evolution of PAH compound distributions, and evaluation of geographic controls. Results suggest that an interplay of multiple geographic factors contribute to the observed variations. Understanding these complex mechanisms is critical to predicting long-term wildfire impacts to water quality in diverse settings.

Sand dams, a water harvesting system built in arid or semi-arid regions, collect and store water in saturated sands to increase water availability in dry seasons, while avoiding evaporation and reducing water-borne disease vectors. The capacity of the dam to store water depends on the texture of the sediment accumulated in the reservoir. An ideal sand dam is expected to wash fine-grained particles, especially silt and clay out of the reservoir, collecting only coarse particles to provide for maximum open pore space and minimum capillary retention (the water is typically extracted via an open well). Although conceptually simple, sand dam commonly failed due to the retention of fine particles. It has been recommended to build sand dams in stages to overcome this problem, with each stage low enough so that the shear forces of flow will keep silt and clay mobile, and pass them out of the reservoir. Although it is effective, this method is not preferred in terms of cost and time spent (repeatedly re-mobilizing a team to add to the dam). We present a new approach to the siltation problem by seeking an ideal shape (weir) cut in the face of a sand dam designed to provide shear forces such that coarse particles accumulation while washing the finer materials such as silt and clay. This will be done by finding a relation between the cut-outs of in the face of the dam and the sediment transport rates. Challenges in predicting sediment transport rate are investigated using both numerical and experimental modeling. We seek to reduce the failure rate of sand dams, and also provide for a method to re-establish sediment fills behind existing dams.

We performed LES simulation of tropical cumulus clouds initialized with soundings from the RICO field project (vanZanten et al. 2011, JAMES). Our analysis concentrated on thermodynamic characteristics of convective clouds, specifically on relationships between the condensation/evaporation rates and cloud micro-physical and dynamical parameters. Such relationships are important for developing parameterizations of the sub-grid latent heat release on the grid size typical for a mesoscale model. The simulation was conducted using an integration domain of 50km; about 2000 clouds were selected for analysis over the course of the 28 hour simulation. The condensation/evaporation rates were analyzed by stratifying the clouds by their size (cloud top). The analyzed parameters included, among others, integral mass and buoyancy flux, cloud and rain water, supersaturation. The results of the analysis revealed a rather remarkable relationship between integral latent heat released in a cloud and cloud’s integral mass flux. This relationship may form the basis for parameterization development of latent heat release.

Soil erosion is a worldwide agricultural and environmental problem that threatens food security and ecosystem viability. In arable environments, the primary cause of soil loss is short and intense storms that are characterized with high spatiotemporal variability. The complex nature of these erosive events imposes a great challenge for erosion modeling and risk analysis. Accurate high-resolution measurement of rain intensity is often lacking or sparsely available. As a result, many studies rely on coarser-resolution rainfall data that often fail to address the impact of intra-storm properties. In this study, based on a novel statistical method, we quantify the discrete and cumulative multiannual impact of rainstorm regime on runoff and soil erosion to better understand the most important rainstorm properties on erosion rate and amount, and, to provide storm-scale risk analyses. Central to our analyses is the coupling of a processes-based crop-land erosion model, Dynamic Water Erosion Prediction Project (DWEPP), with a stochastic rainfall generator that produces localized rainfall statistics at 5-min resolution (CoSMoS). To our knowledge, this is the first study that calibrated DWEPP runoff and sediment at the plot-scale on cropland. The model had an acceptable fit with measured event runoff and sediment data collected in northern Israel (NSE = 0.79 - 0.82). We then generated 300-year stochastic simulations of event-based runoff and sediment yield and used them to estimate erosion risk and calibrate a state-of-the-art frequency analysis method that explicitly accounts for rainstorms occurrence and properties. Results indicate that in the study area, high erosion rate events are characterized by intense rain bursts of short duration (shorter than the usually adopted erosivity index of 30-min), and not necessary by events of large volume accumulation or long duration. On these bases, we proposed an optimal rainfall erosivity index that combines intra-storm properties for the study area. As changes in rainstorm properties are expected under a changing climate, we expect our methodology to be a valuable tool for investigating the global concerns about future changes in soil erosion rate.

Wetlands represent an essential ecosystem, providing flood control, carbon storage, and supporting biodiversity. In particular, the Everglades is a Ramsar Wetland of International Importance, supporting several threatened and endangered species of flora and fauna, and is especially important for wintering birds. Understanding and monitoring wetlands like the Everglades requires the ability to accurately identify and measure wetland extent and change in extent on short time scales. However, in situ methods are difficult given the nature of the surrounding environment, and optical methods of remote sensing are unable to see through dense vegetation. NASA’s Cyclone Global Navigation Satellite System (CYGNSS) has shown promising results using GNSS Reflectometry to identify the presence and extent of inland water. Utilizing GNSS as a signal of opportunity in an L-band passive bistatic radar, it can penetrate rain, clouds, and vegetation. Its 8-satellite constellation exhibits daily or sub-daily revisit rates, enabling the observation of dynamic changes on short time scales. In this work, we utilize a combination of CYGNSS data, ancillary information, and simulations to understand the observability of inundation beneath vegetation. Simulations were used to predict the received power using a water mask derived from Landsat imagery over the Everglades. By analyzing the differences between expected and actual received power, we identified areas of flooded vegetation. These differences were then combined with ancillary data sets to measure seasonal changes and create a seasonal map of open water and inundated vegetation throughout the Everglades network. We also investigated the ability of CYGNSS to discern and measure different vegetation types. Results were then compared with optical and radar imagery and verified with truth data from the Everglades Depth Estimation Network (EDEN) and littoral vegetation maps from the South Florida Water Management District. By leveraging CYGNSS’s high temporal frequency of observations and ability to see under vegetation, measurements of inundated vegetation and its change can complement other remote sensing and in situ methods of wetland monitoring.

Freshwater is limited in the semi-arid Arequipa region in Southern Peru that is home to more than 1.3 million people, agricultural and industrial sectors. To address water demand, eight reservoirs and more than 200 km of water diversion tunnels and canals have been implemented in the Quilca and Camaná river basins, resulting in severely modified hydrology and interconnection of the two basins. The Soil and Water Assessment Tool (SWAT) was used to simulate the current hydrological status and potential alternative management scenarios for the two interconnected basins. Simulation challenges include scarcity of data on soil and land cover to run SWAT, which was addressed by developing publicly available regional soil and land cover databases. A representation of water infrastructure required a complex model structure incorporating point sources to represent water transfers and reservoir outflows and water withdrawals at 17 locations. The developed model is used to provide a comprehensive understanding of water availability in the region under current and alternate scenarios for water regulation. The impact of current water infrastructure on minimum streamflow is explored in the Quilca and Camaná river basins. Results were shared with the local water authorities and the public via an online tool called HidroAQP to support water allocation and related water resource decisions.

Fault zone usually presents a granular gouge, coming from the wear material of previous slips. Considering a mature fault gouge with mineral cementation between particles, we aim to understand the influence of these cohesive links on slip mechanisms. As cohesion is difficult to follow and to quantify with Lab or in-situ experiments, we choose to use Discrete Element Method that has already shown its ability to represent granular gouges with relevant kinematics and rheology. In this work, we consider a dry cohesive contact model in 2D (2x20mm²) involving two rough surfaces representing the rock walls separated by the granular gouge (5000 particles, grain size 27- 260 μm). A step forward compared to literature is to add cohesion on real angular and faceted grains that modifies contact between particles. Focusing on physics of contacts inside the granular gouge, we explore contact interactions and friction coefficient between the different bodies. To represent the cementation we set up a Bonded Mohr-Coulomb law, considering that inter-particular bridges and particles are made with the same material. This numerical model is displacement-driven and is implemented to study the peak of static friction (shape, slope, duration) under a confined pressure of 40 MPa. Depending on the compacity and on the cohesion level of each model, the peak strength may be sharp, short, and intense for dense and highly cohesive cases or smooth, delayed with moderate amplitude for mid-dense and moderately cohesive cases. Three main behaviors are observed: a non-cohesive regime where the added cohesion is too small to truly disturb the global slip mechanism (Couette flow), an intermediate cohesive regime with clusters of cohesive grains, changing the granular flow and acting on slip weakening mechanisms (Riedel shear band R1) and an ultra-cohesive regime where gouge behaves as a brittle material with several Riedel shear bands emergence. We also investigate the role of cohesive bonds in energy budget, focusing on fracture energy term. Three mechanisms are playing a role in fracture energy evolution: the rupture of cohesive bonds, the dilatancy of the gouge and Coulomb dissipations due to friction. These factors are linked to the initial percentage of cohesion inside the sample and help characterize the mechanisms at stake in the initiation of sliding.

Using principal component (PC) analysis of 16 years of monthly series of nitrogen dioxide (NO2) from the Ozone Monitoring Instrument on the Aura satellite, we show that it is the third PC (PC3) from the deseasonalized hierarchy of principal modes that is best coupled with the economic indicators. This coupling is positive, i.e. PC3 and economic indicators manifest positive covariance. However, the economic variability can explain only 40% of the information in PC3. Furthermore, this mode by itself explains only 3% of the total deseasonalized NO2 variability. We thus conclude that, while having an unambiguous impact, the economy can be awarded at best third order of importance in the NO2 departures from the seasonal averages. Once we identified PC3 as the NO2 mode that is coupled with the economic variability, we use this mode as an indicator and look for rapid climate adjustments to that part of NO2 variability that we are confident is coupled with the economic variability. We focus on observational data from the Atmospheric Infrared Sounder (AIRS) on board of NASA Aqua satellite, decompose series of surface skin temperature and clear-sky outgoing longwave radiances (OLR) into principal components, and identify potential impacts of NO2 PC3 on these climate variables.

Rocks of ophiolitic affinity occurring in east Arunachal Pradesh, India consist of a number of dismembered units of mantle peridotites, mafic intrusives, amphibolites, volcano-sedimentaries and meta-carbonates and are considered to be the north-eastern continuation of the Indus-Tsangpo Suture Zone. Petrographical observations of the mantle peridotites include features such as occurrence of two kinds of olivine – larger (0.25mm) showing embayed boundaries and surrounded by smaller olivines (0.12mm) which show cumulate textures, low modal abundance of clinopyroxenes, serpentinized olivine and orthopyroxene, presence of Cr-chlorite surrounding spinels and formation of tremolite at the expense of clinopyroxene. They depict highly refractory geochemical characteristics like low CaO (<0.7 wt%) and TiO2 (<0.08 wt%) values accompanied by Fo content between 0.90 and 0.92 for the larger olivine grains. Low HREE fractionation suggests a moderate to high degree of partial melting (~21%). We also observe selective enrichment in LREEs and HFSEs, extremely high Cr content of metamorphic spinels (0.97-0.99) and high Fo content in recrystallized cumulative olivines (>96).These evidences suggest that peridotites are residual in nature and formed by moderate to high degree of partial melting. They were subjected to interactions with a percolating boninitic melt in the nascent fore-arc of an intra-oceanic subduction zone which caused their re-fertilization in terms of REEs and HFSEs. Later, the peridotites underwent low-temperature fluid-rock interactions during the mature subduction or exhumation stage which caused formation of hydrous minerals like Cr-chlorite and tremolite.

For the first time to our knowledge, the aim of this study is to investigate the spatial variation of atmospheric particulate matter concentrations in Abidjan and Korhogo (Cote d’Ivoire), as well as the relative contribution of PM2.5 to PM10 concentrations from measurement campaigns conducted in dry season in Abidjan and Korhogo. During these campaigns, twenty and fourteen sites were sampled respectively in Abidjan and Korhogo during two working days and one week-end day using portable active analysers. Spatial variations obtained by the IDW interpolation method show that PM10 concentrations are the highest in neighbourhoods without paved roads both in Abidjan and Korhogo whereas the highest PM2.5 concentrations are measured at sites influenced by traffic or wood in domestic fires. PM10 is composed of more than 50% PM2.5 particles in Abidjan, but less than 40% in Korhogo. These proportions are partly due to desert dust and road dust resuspension, which are higher in Korhogo than in Abidjan. The results also show the link between particulate concentrations and living standards in the neighbourhoods. Mean daily profiles of PM10 and PM2.5 concentrations are generally similar in Abidjan and Korhogo from site to site, with peaks in morning and in afternoon. However, in Abidjan, some sites have higher morning peaks than evening peaks, while in Korhogo, all concentration peaks are of the same amplitude. In Abidjan, such a difference may be explained by the fact that road traffic intensity is less spread out in the morning than in the evening. In Korhogo, both the use of firewood and dust resuspension increases aerosol concentrations, especially in the evening. In those conditions, a serious public health problem may be expected in both cities, an impact that we have evaluated by measuring PM2.5 oxidative capacity from DTT (Dithiothreitol) analyses in a few sites.

Determination of biophysical properties of mangroves, e.g. tree height and diameter at breast height, is necessary for assessing mangrove ecosystem dynamics and growth. However, traditional surveying methods (e.g. diameter at breast height, location with GPS, and tree’s height with hypsometer) are time consuming and expensive. In this research we aim to assess mangrove properties by Unmanned Aerial Vehicles (or: UAV/drone) based photogrammetry. The additional benefit of this methodology is that mangrove environments which are often difficult to access can be reached. We focus on Porong Delta, Indonesia. In this area rapid delta progradation has taken place since 2006 due to an extreme mud volcano eruption. The regional climate conditions and added nutrient flux to the new delta have provided a suitable environment for growth of different mangrove species, such as Avicennia spp., Rhizophora spp., and Sonneratia spp. We used an off-the-shelve drone to generate a high-resolution spatial canopy height model (CHM) for the mangroves by using structure-from-motion (SfM) photogrammetry with an achieved DEM resolution of 5.2cm/pixel. This approach is used to determine the structural characteristics of mangrove stands and is validated with ground-truthing on two deltas. The dense point cloud derived from SfM photogrammetry is processed in LAStools and bare earth extraction with a Cloth Simulation Filter method. The CHM is generated from the processed point clouds. The structural information of mangroves is retrieved by using the lidR package in R. Our analysis lead to a median tree height on north and south delta of 4.2m and 3.5m, respectively. Analysis of photogrammetry data shows that drone-based observations of the mangrove canopy height are a useful tool to provide trustworthy data of mangroves characteristics.

Aim of this study is to assess the fidelity of National Center for Medium Range Weather Prediction Unified model’s (NCUM) global (12km) and regional (4km) versions in representing the monsoon sub-seasonal variability over Indian region by applying the process-oriented diagnostics. Moisture budget analysis is performed on the model’s forecast fields for a typical extended monsoon break event occurred during July 2019. The exercise is repeated by using the fifth generation of ECMWF atmospheric reanalysis (ERA5) and the relative roles of the budget terms are quantified. We also tested the budget diagnostics onto the newly generated Indian Monsoon Data Assimilation and Analysis (IMDAA) product. The results obtained here are consistent with our understanding that moisture advection acts a leading term in inducing the break conditions over central Indian and adjoining oceanic regions. Specifically, dry air advection from the northwest regions strongly dries the atmospheric column nearly 7-10 days before and the peak dry phase over Indian subcontinent. Movement of this dryness, with time, towards central India and Arabian Sea is consistent with anomalous total precipitable water content seen from satellite observations. Preliminary results are encouraging and one of the direct implications of this work is that the lead times obtained in the moisture budget assessment can be used for understanding and improvement of the model forecasts.