An improved process-based representation of stream solute transport in the soil and water assessment tools

Hydrological models have long been used to study the interactions between land, surface and groundwater systems, and to predict and manage water quantity and quality. The soil and water assessment tool (SWAT), a widely used hydrological model, can simulate various ecohydrological processes on land and subsequently route the water quality constituents through surface and subsurface waters. So far, in-stream solute transport algorithms of the SWAT model have only been minimally revised, even though it has been acknowledged that an improvement of in-stream process representation can contribute to better model performance with respect to water quality. In this study, we aim to incorporate a new and improved solute transport model into the SWAT model framework. The new process-based model was developed using in-stream process equations from two well established models—the One-dimensional Transport with Inflow and Storage model and the Enhanced Stream Water Quality Model. The modified SWAT model (Mir-SWAT) was tested for water quality predictions in a study watershed in Germany. Compared to the standard SWAT model, Mir-SWAT improved dissolved oxygen (DO) predictions by removing extreme low values of DO (<6 mg/L) simulated by SWAT. Phosphate concentration peaks were reduced during high flows and a better match of daily predicted and measured values was attained using the Mir-SWAT model (R² = 0.17, NSE = −0.65, RSR = 1.29 with SWAT; R² = 0.28, NSE = −0.04, RSR = 1.02 with Mir-SWAT). In addition, Mir-SWAT performed better than the SWAT model in terms of Chlorophyll-a content particularly during winter months, improving the NSE and RSR for monthly average Chl-a by 74 and 42%, respectively. With the new model improvements, we aim to increase confidence in the stream solute transport component of the model, improve the understanding of nutrient dynamics in the stream, and to extend the applicability of SWAT for reach-scale analysis and management.     

An Objective Approach for Prediction of Daily Summer Monsoon Rainfall over Orissa (India) due to Interaction of Mesoscale and Large-scale Synoptic Systems

Orissa State, a meteorological subdivision of India, lies on the east coast of India close to north Bay of Bengal and to the south of the normal position of the monsoon trough. The monsoon disturbances such as depressions and cyclonic storms mostly develop to the north of 15° N over the Bay of Bengal and move along the monsoon trough. As Orissa lies in the southwest sector of such disturbances, it experiences very heavy rainfall due to the interaction of these systems with mesoscale convection sometimes leading to flood. The orography due to the Eastern Ghat and other hill peaks in Orissa and environs play a significant role in this interaction. The objective of this study is to develop an objective statistical model to predict the occurrence and quantity of precipitation during the next 24 hours over specific locations of Orissa, due to monsoon disturbances over north Bay and adjoining west central Bay of Bengal based on observations to up 0300 UTC of the day. A probability of precipitation (PoP) model has been developed by applying forward stepwise regression with available surface and upper air meteorological parameters observed in and around Orissa in association with monsoon disturbances during the summer monsoon season (June-September). The PoP forecast has been converted into the deterministic occurrence/non-occurrence of precipitation forecast using the critical value of PoP. The parameters selected through stepwise regression have been considered to develop quantitative precipitation forecast (QPF) model using multiple discriminant analysis (MDA) for categorical prediction of precipitation in different ranges such as 0.1–10, 11–25, 26–50, 51–100 and >100 mm if the occurrence of precipitation is predicted by PoP model. All the above models have been developed based on data of summer monsoon seasons of 1980–1994, and data during 1995–1998 have been used for testing the skill of the models. Considering six representative stations for six homogeneous regions in Orissa, the PoP model performs very well with percentages of correct forecast for occurrence/non-occurrence of precipitation being about 96% and 88%, respectively for developmental and independent data. The skill of the QPF model, though relatively less, is reasonable for lower ranges of precipitation. The skill of the model is limited for higher ranges of precipitation. accepted September 2006     

Evaluation of Short-Range Forecasts from a Mesoscale Model Over the Indian Region During Monsoon 2006

This study examines the short-range forecast accuracy of the Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) as applied to the July 2006 episode of the Indian summer monsoon (ISM) and the model's sensitivity to the choice of different cumulus parameterization schemes (CPSs), namely Betts-Miller, Grell (GR) and Kain-Fritsch (KF). The results showed that MM5 day 1 (0–24 h prediction) and day 2 (24–48 h prediction) forecasts using all three CPSs overpredicted monsoon rainfall over the Indian landmass, with the larger overprediction seen in the day 2 forecasts. Among the CPSs, the rainfall distribution over the Indian landmass was better simulated in forecasts using the KF scheme. The KF scheme showed better skill in predicting the area of rainfall for most of the rainfall thresholds. The root mean square error (RMSE) in day 1 and day 2 rainfall forecasts using different CPSs showed that rainfall simulated using the KF scheme agreed better with the observed rainfall. As compared to other CPSs, simulation using the GR scheme showed larger RMSE in wind speed prediction at 850 and 200 hPa over the Indian landmass. MM5 24-h temperature forecasts at 850 hPa with all the CPSs showed a warm bias of the order of 1 K over the Indian landmass and the bias doubled in 48-h model forecasts. The mean error in temperature prediction at 850 hPa over the Indian region using the KF scheme was comparatively smaller for all the forecast intervals. The model with all the CPSs overpredicted humidity at 850 hPa. The improved prediction by MM5 with the KF scheme is well complemented by the smaller error shown by the KF scheme in vertical distribution of heat and mean moist static energy in the lower troposphere. In this study, the KF scheme which explicitly resolve the downdrafts in the cloud column tended to produce more realistic precipitation forecasts as compared to other schemes which did not explicitly incorporate downdraft effects. This is an important result especially given that the area covered by monsoon-precipitating systems is largely from stratiform-type clouds which are associated with strong downdrafts in the lower levels. This result is useful for improving the treatment of cumulus convection in numerical models over the ISM region.     

Scales and structure of frontal adjustment and freshwater export in a region of freshwater influence

Sea surface temperature satellite imagery and a regional hydrodynamic model are used to investigate the variability and structure of the Liverpool Bay thermohaline front. A statistically based water mass classification technique is used to locate the front in both data sets. The front moves between 5 and 35 km in response to spring–neap changes in tidal mixing, an adjustment that is much greater than at other shelf-sea fronts. Superimposed on top of this fortnightly cycle are semi-diurnal movements of 5–10 km driven by flood and ebb tidal currents. Seasonal variability in the freshwater discharge and the density difference between buoyant inflow and more saline Irish Sea water give rise to two different dynamical regimes. During winter, when cold inflow reduces the buoyancy of the plume, a bottom-advected front develops. Over the summer, when warm river water provides additional buoyancy, a surface-advected plume detaches from the bottom and propagates much larger distances across the bay. Decoupled from near-bed processes, the position of the surface front is more variable. Fortnightly stratification and re-mixing over large areas of Liverpool Bay is a potentially important mechanism by which freshwater, and its nutrient and pollutant loads, are exported from the coastal plume system. Based on length scales estimated from model and satellite data, the erosion of post-neap stratification is estimated to be responsible for exporting approximately 19% of the fresh estuarine discharge annually entering the system. Although the baroclinic residual circulation makes a more significant contribution to freshwater fluxes, the episodic nature of the spring–neap cycle may have important implications for biogeochemical cycles within the bay.     

Storm surge simulation along the U.S. East and Gulf Coasts using a multi-scale numerical model approach

The effectiveness of simulating surge inundation using the Eulerian–Lagrangian circulation (ELCIRC) model over multi-scale unstructured grids was examined in this study. The large domain model grid encompasses the western North Atlantic Ocean, the Gulf of Mexico, and the Caribbean Sea to appropriately account for remote and resonance effects during hurricane events and simplify the specification of the open boundary condition. The U.S. East and Gulf Coasts were divided into 12 overlapping basins with fine-resolution (up to 30 × 30 m) grids to model overland surge flooding. These overlapping basins have different fine-resolution grids near the coastal region, but have an identical coarse-resolution grid in the offshore region within the large model domain. Thus, the storm surge prediction can be conducted without reducing computation efficiency by executing multiple model runs with local fine-resolution grids where potential hurricane landfalls may occur. The capability of the multi-scale approach was examined by simulating storm surge caused by Hurricanes Andrew (1992) and Isabel (2003) along the South Florida coast and in the Chesapeake Bay. Comparisons between simulated and observed results suggest that multi-scale models proficiently simulated storm surges in the Biscayne Bay and the Chesapeake Bay during two hurricanes. A series of sensitivity tests demonstrated that the simulation of surge flooding was improved when LiDAR topographic data and special bottom drag coefficient values for mangrove forests were employed. The tests also showed that appropriate representation of linear hydrologic features is important for computing surge inundation in an urban area.     

Radon as an indicator of limited cross-shelf mixing of submarine groundwater discharge along an open ocean beach in the South Atlantic Bight during observed hypoxia

Hypoxic conditions (dissolved oxygen (DO)<2 mg l⁻¹) have been documented in the nearshore coastal waters of Long Bay, South Carolina, United States of America, during summer months over the past several years. Hypoxia was documented in August 2009 in the nearshore (<500 m offshore) for ten consecutive days and four days in September 2009 corresponding with spring tides. This study measured radon activities of shallow beachface groundwater and nearshore bottom waters to estimate mixing rates and submarine groundwater discharge (SGD) in the nearshore waters of central Long Bay. Statistical analyses demonstrate significant correlations between high bottom water radon activities, low DO, and cooler bottom water temperatures during hypoxic conditions. Elevated radon activities during hypoxia were significantly influenced by upwelling favorable conditions which severely limited cross-shelf mixing. Model results indicate mixing of nearshore and offshore waters was limited by up to 93% (range: 43-100%) relative to non-hypoxic conditions. Data suggests previously overlooked natural phenomena including limited cross-shelf mixing and SGD can significantly influence nearshore water quality.     

The modification of current ellipses by stratification in the Liverpool Bay ROFI

Understanding the fate of freshwater runoff and corresponding nutrient and pollution loads is of critical importance for the development of accurate predictive models and coastal management tools. A key element of such studies is the identification and understanding of the interaction between stratification and current structure. This paper presents a new series of measurements made in the Liverpool Bay region of freshwater influence (ROFI) during spring 2004 where freshwater-maintained horizontal density gradients and strong tidal currents interact to produce strain-induced periodic stratification (SIPS). During stratification, tidal current profiles are significantly modified such that the tidal flow deviates from the otherwise rectilinear E–W axis generating counter rotating upper and lower mixed layers. This feature has often been reported for the Rhine ROFI but not previously identified in Liverpool Bay despite previous investigation at this site. Investigation of an ongoing long-term dataset collected nearby reveals this process to be a common feature throughout the year. Liverpool Bay is shown to maintain three different regimes, long term mixed, long term stratified, and a transitional state when SIPS occurs. The phase of SIPS relative to the tide results in a residual flow away from the Welsh coastline in the upper water column of 2.3–3.6 cm s⁻¹ with a counterflow in the lower layer of 2.8–3.1 cm s⁻¹ towards the coast.     

Spatiotemporal variability of hypoxia and eutrophication in Manila Bay,Philippines during the northeast and southwest monsoons

Hypoxia in Manila Bay, Philippines was previously reported during the northeast monsoon (dry season) in February 2010. In this study, four more field surveys of the same 31 stations were conducted in July 2010, August 2011 and 2012 (wet season, southwest monsoon), and February 2011 (dry season, northeast monsoon). During the wet season, bottom hypoxia spread northward towards the coast with dissolved oxygen (DO) ranging from 0.12 to 9.22 mg/L and the bay-wide average reaching 2.10 mg/L. Nutrient levels were elevated, especially near the bottom where dissolved inorganic nitrogen reached 22.3 μM (July 2010) and phosphorus reached 5.61 μM (August 2011). High nutrient concentrations often coincided with low near-bottom DO content. Our work builds on the preliminary assessment of hypoxia in Manila Bay, the importance of repeated temporal studies, and shows hypoxia to prevail significantly during the southwest monsoon (wet season) when increased freshwater discharge caused strong water column stratification.     

Development,implementation, and skill assessment of the NOAA/NOS Great Lakes Operational Forecast System

The NOAA Great Lakes Operational Forecast System (GLOFS) uses near-real-time atmospheric observations and numerical weather prediction forecast guidance to produce three-dimensional forecasts of water temperature and currents, and two-dimensional forecasts of water levels of the Great Lakes. This system, originally called the Great Lakes forecasting system (GLFS), was developed at The Ohio State University and NOAA’s Great Lakes Environmental Research Laboratory (GLERL) in 1989. In 1996, a workstation version of the GLFS was ported to GLERL to generate semi-operational nowcasts and forecasts daily. In 2004, GLFS went through rigorous skill assessment and was transitioned to the National Ocean Service (NOS) Center for Operational Oceanographic Products and Services (CO-OPS) in Silver Spring, MD. GLOFS has been making operational nowcasts and forecasts at CO-OPS since September 30, 2005. Hindcast, nowcast, and forecast evaluations using the NOS-developed skill assessment software tool indicated both surface water levels and temperature predictions passed the NOS specified criteria at a majority of the validation locations with relatively low root mean square error (4–8 cm for water levels and 0.5 to 1°C for surface water temperatures). The difficulty of accurately simulating seiches generated by storms (in particular in shallow lakes like Lake Erie) remains a major source of error in water level prediction and should be addressed in future improvements of the forecast system.     

Improvement of hydrodynamic forecasting of Danish waters: impact of low-frequency North Atlantic barotropic variations

The Danish Maritime Safety Administration (DaMSA) provides forecast of elevations, currents, and other parameters to the maritime society. Accurate and reliable predictions are important to help navigate Danish waters in a safe manner, and the forecasts are routinely used by the Vessel Traffic Services in the Great Belt and the Sound. The DaMSA model setup includes three nested models, with coarse resolution in the North Atlantic and increasing to 600 m in the Belt Sea and South West Baltic. Observations of some special events in late 2009 drew attention to a possible relation between Atlantic-scale surge events and small-scale currents in the Danish Straits. During the special event with large-scale surge, the observed southward moving current in the Danish Straits was 0.5–2.0 m/s for several days, while the operational model showed a much smaller response. As a consequence, the entire DaMSA model complex was revised during 2010. Multi-annual reruns have showed that with the updated model, the explained variance of the current increases from 67% to 88%.     

Organic matter governs N and P balance in Danube Delta lakes

The transformation of dissolved inorganic nitrogen (DIN) and soluble reactive phosphorous (SRP), and the release of dissolved organic and particulate N and P, were analyzed in two lake complexes (Uzlina–Isac and Puiu–Rosu–Rosulet) of the Danube Delta wetland during flood conditions in May and at low water level in September 2006. The Uzlina–Isac complex was hydrologically tightly-connected with the Danube River and was flushed with river-borne nutrients and organic matter. These lakes acted as effective transformers for nutrients and produced large amounts of fresh biomass, that promoted the excretion of dissolved organic N and P during active growth. Biomass breakdown created particulate matter (<0.45 μm), which was widely liberated during low flow in the fall. The Puiu–Rosu–Rosulet complex was characterized by a more distant position to the Danube and proximity to the Black Sea, and received dominantly transformed organic compounds from the flow-through water and vast vegetation cover. Due to reduced nutrient input, the internal production of organic biomass also was reduced in these more remote lakes. Total N and P export from the lake nearest to the shelf was governed by dominantly dissolved organic and particulate compounds (mean 58 and 82%, respectively). Overall, this survey found that these highly productive wetlands efficiently transform nutrients into a large pool of dissolved organic and particulate N and P. Hence, wetland lakes may behave widely as net sources of organic N and P to downstream waters and coastal marine systems.     

A long-term earthquake forecast for the Kuril-Kamchatka arc for the period from September 2010 to August 2015 and the reliability of previous forecasts,as well as their applications

We describe results from the ongoing 2008–2010 work on long-term earthquake prediction for the Kuril-Kamchatka arc based on the patterns of seismic gaps and the seismic cycle. We provide a forecast for the next 5 years, September 2010 to August 2015, specified for all segments of the earthquake-generating Kuril-Kamchatka arc zone. For 20 segments we predict the phases of the seismic cycle, the normalized rate of small earthquakes (A₁₀), the magnitudes of moderate earthquakes to be expected with probabilities of 0.8, 0.5, and 0.15, the maximum possible magnitudes, and the probabilities of great (M ≥ 7.7) earthquakes. It is shown that the forecast given for the previous 5 years, from September 2005 to September 2010, was found to be accurate. We report the measures that were taken for seismic safety and retrofitting based on these forecasts.     

The predictability of near-coastal currents using a baroclinic unstructured grid model

A limited domain, coastal ocean forecast system consisting of an unstructured grid model, a meteorological model, a regional ocean model, and a global tidal database is designed to be globally relocatable. For such a system to be viable, the predictability of coastal currents must be well understood with error sources clearly identified. To this end, the coastal forecast system is applied at the mouth of Chesapeake Bay in response to a Navy exercise. Two-day forecasts are produced for a 10-day period from 4 to 14 June 2010 and compared to real-time observations. Interplay between the temporal frequency of the regional model boundary forcing and the application of external tides to the coastal model impacts the tidal characteristics of the coastal current, even contributing a small phase error. Frequencies of at least 3 h are needed to resolve the tidal signal within the regional model; otherwise, externally applied tides from a database are needed to capture the tidal variability. Spatial resolution of the regional model (3 vs 1 km) does not impact skill of the current prediction. Tidal response of the system indicates excellent representation of the dominant M ₂ tide for water level and currents. Diurnal tides, especially K ₁, are amplified unrealistically with the application of coarse 27-km winds. Higher-resolution winds reduce current forecast error with the exception of wind originating from the SSW, SSE, and E. These winds run shore parallel and are subject to strong interaction with the shoreline that is poorly represented even by the 3-km wind fields. The vertical distribution of currents is also well predicted by the coastal model. Spatial and temporal resolution of the wind forcing including areas close to the shoreline is the most critical component for accurate current forecasts. Additionally, it is demonstrated that wind resolution plays a large role in establishing realistic thermal and density structures in upwelling prone regions.     

First Order Seismic Microzonation of Haldia, Bengal Basin (India) Using a GIS Platform

The seismic microzonation of the Bengal Basin, Haldia region, India is carried out using the Analytical Hierarchy Process (AHP) on the Geographic Information System (GIS). Three themes are used for the seismic microzonation, namely Peak Ground Acceleration (PGA), predominant frequency and elevation map. An analysis of the maximum magnitude (m _max) and the b value is carried out after preparing the earthquake catalogue from various sources. On the basis of the tectonic set up and seismicity of the region, five seismic zones are delineated which can be a threat to Haldia. They are broadly classified as Zone 1: Arakan-Yoma Zone (AYZ), Zone 2: Himalayan Zone (HZ), Zone 3: Shillong Plateau Zone (SPZ), Zone 4: Bay of Bengal Zone (BBZ) and Zone 5: Shield Zone (SZ). The m _max for Zones 1, 2, 3, 4 and 5 are 8.30 ± 0.51, 9.09 ± 0.58, 9.20 ± 0.51, 6.62 ± 0.43 and 6.61 ± 0.43, respectively. The PGA value is computed for Haldia following the attenuation relationship taking the m _max of each source zone. The expected PGA at Haldia varies from 0.09–0.19 g. The predominant frequency of Haldia is also calculated using the H/V ratio with a frequency ranging from 0.1–3.0 Hz. The elevation map of Haldia is also generated using the Shuttle Radar Topography Mission (STRM) data. A first-order seismic microzonation map of Haldia is prepared in which four zones of hazard have been broadly classified for Haldia as very high seismic hazard zone, high seismic hazard zone, moderate seismic hazard zone and less seismic hazard zone. The very high seismic hazard zone is observed along the southern part of Haldia where there are major industrial and port facilities. The PGA for the four hazard zones are: 0.09–0.13 g for low hazard zone, > 0.13–0.15 g for moderate hazard zone, > 0.15–0.16 g for high hazard zone and > 0.16–0.19 g for very high hazard zone.     

“Dead Zone” dynamics in Lake Erie: the importance of weather and sampling intensity for calculated hypolimnetic oxygen depletion rates

Calculated hypolimnetic oxygen depletion (HOD) rates depend not only on environmental factors but also logistical ones. In particular, lack of understanding of the effects of weather in addition to how sampling effort determines calculated HOD rates complicates ecological understanding and environmental management of lake ecosystems. To better determine the roles of weather and sampling effort, we combined (1) weekly measurements of temperature and dissolved oxygen (DO) concentrations from seven stations in the Sandusky subbasin of Lake Erie’s central basin during 2005, (2) contemporaneous measures of storm activity and tributary discharge, and (3) a two-dimensional coupled hydrodynamic, chemical, and biological model of Lake Erie to investigate (1) how increased storm activity and tributary discharge affected short- (daily) and long-term (seasonal) dynamics of hypolimnetic hypoxia, and (2) how spatial (number of sites sampled) and temporal (sampling frequency) sampling effort affected calculated HOD rates. Our model closely replicated field-observed DO dynamics. When comparing baseline modeled dynamics to those in a second simulation with twice the number of days with high winds, however, we found that with more storm activity (1) periods of entrainment became more frequent, (2) the hypolimnion was warmer, (3) thermal stratification occurred 1 month later, whereas autumnal turnover occurred at least 1 week earlier shortening the duration of stratification by 1–2 months, and (4) HOD rates increased 12%. Further, spatial and temporal sampling intensity also affected calculated HOD rates. Consequently, adequately quantifying actual HOD rates requires sufficient sampling effort and the particular role of weather should be assessed with rigorous field and simulation studies, especially if HOD rates are used to indicate management success.     

Spatial patterning of water quality in Biscayne Bay, Florida as a function of land use and water management

An objective classification analysis was performed on a water quality data set from 25 sites collected monthly during 1994-2003. The water quality parameters measured included: TN, TON, DIN, NH4+, NO3-, NO2-, TP, SRP, TN:TP ratio, TOC, DO, CHL A, turbidity, salinity and temperature. Based on this spatial analysis, Biscayne Bay was divided into five zones having similar water quality characteristics. A robust nutrient gradient, driven mostly by dissolved inorganic nitrogen, from alongshore to offshore in the main Bay, was a large determinant in the spatial clustering. Two of these zones (Alongshore and Inshore) were heavily influenced by freshwater input from four canals which drain the South Dade agricultural area, Black Point Landfill, and sewage treatment plant. The North Bay zone, with high turbidity, phytoplankton biomass, total phosphorus, and low DO, was affected by runoff from five canals, the Munisport Landfill, and the urban landscape. The South Bay zone, an embayment surrounded by mangrove wetlands with little urban development, was high in dissolved organic constituents but low in inorganic nutrients. The Main Bay was the area most influenced by water exchange with the Atlantic Ocean and showed the lowest nutrient concentrations. The water quality in Biscayne Bay is therefore highly dependent of the land use and influence from the watershed.     

Assessing the spatial and temporal variability of dissolved organic matter in Liverpool Bay using excitation–emission matrix fluorescence and parallel factor analysis

The spatial and diurnal tidal variability of dissolved organic carbon (DOC) concentrations and the composition of dissolved organic matter (DOM), as evaluated by high-temperature catalytic oxidation and excitation–emission matrix combined with parallel factor analysis (EEM–PARAFAC), respectively, were determined in Liverpool Bay. EEM–PARAFAC modeling resulted in six fluorescent components characterized as terrestrial humic-like (two), microbial humic-like (two), and protein-like (two). The spatial distributions of DOC and the four humic-like components were negatively correlated with salinity in the high-salinity waters observed in this study (30.41–33.75), suggesting that terrestrial DOM was conservatively distributed. The spatial patterns of protein-like components were largely different from those of DOC, humic-like components, and chlorophyll a, suggesting that these distributions were the combined result of production and degradation in the bay in addition to river inputs. These findings suggest that the DOM dynamics in Liverpool Bay are strongly controlled by river-dominated allochthonous DOM inputs with some less significant contributions of autochthonous DOM within the bay. In addition, the temporal variations of DOM associated with the diurnal tidal cycles were determined at one inshore (31.34–32.24 salinity) and one offshore (33.64–33.75 salinity) station in the bay. Negative linear relationships between salinity and DOM characteristics, i.e., DOC, humic-like, and protein-like components, were observed at the inshore station. In contrast, no relationship was observed at the offshore station, suggesting that the export of DOM through rivers and possibly tidal flats have a noticeable influence on DOM concentration and composition up to a relatively elevated salinity of around 33 in Liverpool Bay.     

Can Sea Fog be Inferred from Operational GEM Forecast Fields?

Three cases of widespread sea fog in Lunenburg Bay, Nova Scotia were used to evaluate the suitability of operational regional GEM forecast fields for inferring advection fog occurrences. Verification scores suggest that the objective analyses contain significant departures from observations that will affect model accuracy, given the sensitivity of fog condensation microphysics. Dew point depression (ES) scores show larger differences compared to temperature, with both influenced by surface characteristics. For objective analyses and GEM forecasts ES < 2 C seems to match fog satellite images better than the physical threshold ES ≤ 0 C. In addition the GEM forecasts show a general tendency towards drier conditions near the surface, therefore reconfiguring GEM to better represent condensation in the boundary layer is proposed.     

A data-based regional scale autoregressive rainfall-runoff model: a study from the Odra River

This paper aims to compare the performances of multivariate autoregressive (MAR) techniques and univariate autoregressive (AR) methods applied to regional scale rainfall-runoff modelling. We focus on the case study from the upper and middle reaches of the Odra River with its main tributaries in SW Poland. The rivers drain both the mountains (the Sudetes) and the lowland (Nizina Śląska). The region is exposed to extreme hydrologic and meteorological events, especially rain-induced and snow-melt floods. For the analysis, four hydrologic and meteorological variables are chosen, i.e., discharge (17 locations), precipitation (7 locations), thickness of snow cover (7 locations) and groundwater level (1 location). The time period is November 1971–December 1981 and the temporal resolution of the time series is of 1 day. Both MAR and AR models of the same orders are fitted to various subsets of the data and subsequently forecasts of discharge are derived. In order to evaluate the predictions the stepwise procedure is applied to make the validation independent of the specific sample path of the stochastic process. It is shown that the model forecasts peak discharges even 2–4 days in advance in the case of both rain-induced and snow-melt peak flows. Furthermore, the accuracy of discharge predictions increases if one analyses the combined data on discharge, precipitation, snow cover, and groundwater level instead of the pure discharge multivariate time series. MAR-based discharge forecasts based on multivariate data on discharges are more accurate than AR-based univariate predictions for a year with a flood, however, this relation is reverse in the case of the free-of-flooding year. In contrast, independently of the occurrence of floods within a year, MAR-based discharge forecasts based on discharges, precipitation, snow cover, and groundwater level are more precise than AR-based predictions.