scholarly journals Homogenization of Norwegian monthly precipitation series

2021 ◽  
Author(s):  
Elinah Khasandi Kuya ◽  
Herdis Motrøen Gjelten ◽  
Ole Einar Tveito
Keyword(s):  
Large Scale ◽  
Linear Trend ◽  
Spatial Coherence ◽  
Network Activity ◽  
Monthly Precipitation ◽  
Precipitation Series ◽  
Climate Services ◽  
Observation Network ◽  
Precipitation Gauge ◽  
Increasing Trends

<p>Climate normals play an important role in weather and climate studies and therefore require high-quality dataset that is both consistent and homogenous. The Norwegian observation network has changed considerably during the last 20-30 years, introducing non-climatic changes such as automation and relocation. Homogenization was therefore necessary and work has been done at the Norwegian Meteorological Institute to establish a homogeneous precipitation reference dataset for the purpose of calculating the new climatological standard normals for the period 1991-2020. </p><p>The homogenization tool Climatol was applied to detect inhomogeneities in the Norwegian precipitation series, for the period 1961-2018. 370 series (including 44 from Sweden and one from Finland) of monthly precipitation sums, from the ClimNorm precipitation dataset were used in the homogenization analysis. ClimNorm is an international network activity under the Nordic Framework for Climate Services covering six countries in the Nordic region (Denmark, Estonia, Finland, Latvia, Norway and Sweden) with an objective that includes sharing data, methods and experiences in preparing a data basis as good as possible for calculation of new climate normals. </p><p>Results from homogeneity testing found inhomogeneities in 95 (29 %) of the 325 Norwegian precipitation series. However, only 81 (25 %) of the series were classified as inhomogeneous after conferring with metadata and therefore adjusted. Relocation of the precipitation gauge and automation were the main causes of all the inhomogeneities in the Norwegian series, explaining 71 % and 12 % respectively of all detected breaks. All but one of the accepted inhomogeneities could be confirmed with metadata. Inhomogeneities found in the Swedish and Finnish series were adjusted without metadata. Results further showed benefits of incorporating metadata to the automatically detected inhomogeneities. Linear trend analysis showed increasing trends in the period 1961-2018 except in autumn where a decreasing trend was observed. The homogeneity analysis produced a 58-year long homogenous dataset for 325 monthly precipitation sum with regional temporal variability and spatial coherence that was significantly better than that of non-homogenized series. The homogenized dataset is more reliable in explaining the large-scale climate variations and was used to calculate the new climate normals in Norway.</p>

Estimation and Extrapolation of Climate Normals and Climatic Trends

2007 ◽  
Vol 46 (11) ◽  
pp. 1759-1776 ◽  
Author(s):  
Robert E. Livezey ◽  
Konstantin Y. Vinnikov ◽  
Marina M. Timofeyeva ◽  
Richard Tinker ◽  
Huug M. van den Dool
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Global Climate ◽  
Linear Trend ◽  
Linear Component ◽  
Climate Services ◽  
Climate Record ◽  
Current Climate ◽  
Starting Point ◽  
The Future

Abstract WMO-recommended 30-yr normals are no longer generally useful for the design, planning, and decision-making purposes for which they were intended. They not only have little relevance to the future climate, but are often unrepresentative of the current climate. The reason for this is rapid global climate change over the last 30 yr that is likely to continue into the future. It is demonstrated that simple empirical alternatives already are available that not only produce reasonably accurate normals for the current climate but also often justify their extrapolation to several years into the future. This result is tied to the condition that recent trends in the climate are approximately linear or have a substantial linear component. This condition is generally satisfied for the U.S. climate-division data. One alternative [the optimal climate normal (OCN)] is multiyear averages that are not fixed at 30 yr like WMO normals are but rather are adapted climate record by climate record based on easily estimated characteristics of the records. The OCN works well except with very strong trends or longer extrapolations with more moderate trends. In these cases least squares linear trend fits to the period since the mid-1970s are viable alternatives. An even better alternative is the use of “hinge fit” normals, based on modeling the time dependence of large-scale climate change. Here, longer records can be exploited to stabilize estimates of modern trends. Related issues are the need to avoid arbitrary trend fitting and to account for trends in studies of ENSO impacts. Given these results, the authors recommend that (a) the WMO and national climate services address new policies for changing climate normals using the results here as a starting point and (b) NOAA initiate a program for improved estimates and forecasts of official U.S. normals, including operational implementation of a simple hybrid system that combines the advantages of both the OCN and the hinge fit.

scholarly journals Development of the homogenized monthly precipitation series during 1910–2014 and its changes in Hunan Province, China

2017 ◽  
Vol 8 (4) ◽  
pp. 791-801 ◽  
Author(s):  
Jiadong Peng ◽  
Yufang Liao ◽  
Yuanhua Jiang ◽  
Jianming Zhang ◽  
Xingren Qi
Keyword(s):  
Time Series ◽  
Abrupt Change ◽  
Linear Trend ◽  
Periodic Oscillation ◽  
Hunan Province ◽  
Monthly Precipitation ◽  
Precipitation Series ◽  
Precipitation Time Series ◽  
Significant Linear Trend ◽  
Complete Precipitation

Abstract Based on the statistical method and the historical evolution of meteorological stations, the precipitation time series for each station in Hunan Province of China during 1910–2014 are tested for their homogeneity and then adjusted. The missing data caused by war and other reasons at the eight meteorological stations which had records before 1950 is filled by interpolation using adjacent observations, and complete precipitation time series since the establishment of stations are constructed. After that, according to the representative analysis of each station in different time periods, the precipitation series of Hunan Province during 1910–2014 are built and changes are analyzed. The results indicate that the annual precipitation has no significant linear trend but has obvious inter-decadal fluctuation during 1910–2014 and a periodic oscillation of 20 years is the most significant. Precipitation in winter (DJF) and summer (JJA) shows a slight wetter trend, and a slight dryer trend in spring (MAM) and autumn (SON). Abrupt change test suggests that annual and seasonal precipitations except for MAM and SON have abrupt ascending changes in the recent 100 years.

DESIGN AND IMPLEMENTATION OF THE OCEANOGRAPHIC MODELING AND OBSERVATION NETWORK (REMO) FOR PHYSICAL OCEANOGRAPHY STUDIES AND OCEAN FORECASTING

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Jose Antonio Moreira Lima
Keyword(s):  
Atlantic Ocean ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Integrated Approach ◽  
Sea Surface ◽  
Global Ocean ◽  
Height Anomaly ◽  
The North ◽  
Observation Network ◽  
Ocean Forecasting

This paper is concerned with the planning, implementation and some results of the Oceanographic Modeling and Observation Network, named REMO, for Brazilian regional waters. Ocean forecasting has been an important scientific issue over the last decade due to studies related to climate change as well as applications related to short-range oceanic forecasts. The South Atlantic Ocean has a deficit of oceanographic measurements when compared to other ocean basins such as the North Atlantic Ocean and the North Pacific Ocean. It is a challenge to design an ocean forecasting system for a region with poor observational coverage of in-situ data. Fortunately, most ocean forecasting systems heavily rely on the assimilation of surface fields such as sea surface height anomaly (SSHA) or sea surface temperature (SST), acquired by environmental satellites, that can accurately provide information that constrain major surface current systems and their mesoscale activity. An integrated approach is proposed here in which the large scale circulation in the Atlantic Ocean is modeled in a first step, and gradually nested into higher resolution regional models that are able to resolve important processes such as the Brazil Current and associated mesoscale variability, continental shelf waves, local and remote wind forcing, and others. This article presents the overall strategy to develop the models using a network of Brazilian institutions and their related expertise along with international collaboration. This work has some similarity with goals of the international project Global Ocean Data Assimilation Experiment OceanView (GODAE OceanView).

Plan for the development of specialized climate forecasting in NEACC

2021 ◽  
pp. 101-111
Author(s):  
S.V. Emelina ◽  
◽  
V.M. Khan ◽  
Keyword(s):  
Large Scale ◽  
Regional Climate ◽  
Optimal Strategies ◽  
Economic Sectors ◽  
Climate Services ◽  
Climate Conditions ◽  
Climate Risks ◽  
The North ◽  
Weather And Climate ◽  
North Eurasia

The possibility of developing specialized seasonal forecasting within the framework of the North Eurasia Climate Centre is discussed. The purpose of these forecasts is to access the impacts of significant large-scale anomalies of meteorological elements on various economic sectors for the timely informing of government services and private businesses to select optimal strategies for planning preventive measures. A brief overview of the groups of climatic risks in the context of the impacts on the socio-economic sphere is given according to the Russian and foreign bibliographic sources. Examples of the activities of some Regional Climate Centers that produce forecast information with an assessment of possible impacts of weather and climate conditions at seasonal scales on various human activities are given. Keywords: climate services, regional climate forums, weather and climate risks, North Eurasia Climate Centre

Skill assessment of post-processing methods for ECMWF SEAS5 seasonal forecasts over Europe

2021 ◽  
Author(s):  
Alice Crespi ◽  
Marcello Petitta ◽  
Lucas Grigis ◽  
Paola Marson ◽  
Jean-Michel Soubeyroux ◽  
...  
Keyword(s):  
Large Scale ◽  
Production Management ◽  
Spatial Scales ◽  
Research Field ◽  
Skill Assessment ◽  
Post Processing ◽  
Seasonal Forecasts ◽  
Climate Services ◽  
Local Climate ◽  
Climate Conditions

<p>Seasonal forecasts provide information on climate conditions several months ahead and therefore they could represent a valuable support for decision making, warning systems as well as for the optimization of industry and energy sectors. However, forecast systems can be affected by systematic biases and have horizontal resolutions which are typically coarser than the spatial scales of the practical applications. For this reason, the reliability of forecasts needs to be carefully assessed before applying and interpreting them for specific applications. In addition, the use of post-processing approaches is recommended in order to improve the representativeness of the large-scale predictions of regional and local climate conditions. The development and evaluation downscaling and bias-correction procedures aiming at improving the skills of the forecasts and the quality of derived climate services is currently an open research field. In this context, we evaluated the skills of ECMWF SEAS5 forecasts of monthly mean temperature, total precipitation and wind speed over Europe and we assessed the skill improvements of calibrated predictions.</p><p>For the calibration, we combined a bilinear interpolation and a quantile mapping approach to obtain corrected monthly forecasts on a 0.25°x0.25° grid from the original 1°x1° values. The forecasts were corrected against the reference ERA5 reanalysis over the hindcast period 1993–2016. The processed forecasts were compared over the same domain and period with another calibrated set of ECMWF SEAS5 forecasts obtained by the ADAMONT statistical method.</p><p>The skill assessment was performed by means of both deterministic and probabilistic verification metrics evaluated over seasonal forecasted aggregations for the first lead time. Greater skills of the forecast systems in Europe were generally observed in spring and summer, especially for temperature, with a spatial distribution varying with the seasons. The calibration was proved to effectively correct the model biases for all variables, however the metrics not accounting for bias did not show significant improvements in most cases, and in some areas and seasons even small degradations in skills were observed.</p><p>The presented study supported the activities of the H2020 European project SECLI-FIRM on the improvement of the seasonal forecast applicability for energy production, management and assessment.</p>

scholarly journals DEVELOPMENT OF A HIGH-SPEED VIDEOGRAMMETRIC MEASUREMENT SYSTEM WITH APPLICATION IN LARGE-SCALE SHAKING TABLE TEST

2019 ◽  
Vol IV-2/W7 ◽  
pp. 33-38
Author(s):  
S. Gao ◽  
Z. Ye ◽  
C. Wei ◽  
X. Liu ◽  
X. Tong
Keyword(s):  
Data Processing ◽  
Measurement System ◽  
High Speed ◽  
Large Scale ◽  
Moving Objects ◽  
Shaking Table Test ◽  
Image Sequences ◽  
Shaking Table ◽  
Dynamic Monitoring ◽  
Observation Network

<p><strong>Abstract.</strong> The high-speed videogrammetric measurement system, which provides a convenient way to capture three-dimensional (3D) dynamic response of moving objects, has been widely used in various applications due to its remarkable advantages including non-contact, flexibility and high precision. This paper presents a distributed high-speed videogrammetric measurement system suitable for monitoring of large-scale structures. The overall framework consists of hardware and software two parts, namely observation network construction and data processing. The core component of the observation network is high-speed cameras to provide multiview image sequences. The data processing part automatically obtains the 3D structural deformations of the key points from the captured image sequences. A distributed parallel processing framework is adopted to speed up the image sequence processing. An empirical experiment was conducted to measure the dynamics of a double-tube five-layer building structure on the shaking table using the presented videogrammetric measurement system. Compared with the high-accuracy total station measurement, the presented system can achieve a sub-millimeter level of coordinates discrepancy. The 3D deformation results demonstrate the potential of the non-contact high-speed videogrammetric measurement system in dynamic monitoring of large-scale shake table tests.</p>

scholarly journals Large-scale atmospheric forcing and topographic modification of precipitation rates over High Asia – a neural-network-based approach

2015 ◽  
Vol 6 (1) ◽  
pp. 61-81 ◽  
Author(s):  
L. Gerlitz ◽  
O. Conrad ◽  
J. Böhner
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
Large Scale ◽  
Local Scale ◽  
Predictor Variables ◽  
High Mountain ◽  
Target Area ◽  
Monthly Precipitation ◽  
Highly Nonlinear

Abstract. The heterogeneity of precipitation rates in high-mountain regions is not sufficiently captured by state-of-the-art climate reanalysis products due to their limited spatial resolution. Thus there exists a large gap between the available data sets and the demands of climate impact studies. The presented approach aims to generate spatially high resolution precipitation fields for a target area in central Asia, covering the Tibetan Plateau and the adjacent mountain ranges and lowlands. Based on the assumption that observed local-scale precipitation amounts are triggered by varying large-scale atmospheric situations and modified by local-scale topographic characteristics, the statistical downscaling approach estimates local-scale precipitation rates as a function of large-scale atmospheric conditions, derived from the ERA-Interim reanalysis and high-resolution terrain parameters. Since the relationships of the predictor variables with local-scale observations are rather unknown and highly nonlinear, an artificial neural network (ANN) was utilized for the development of adequate transfer functions. Different ANN architectures were evaluated with regard to their predictive performance. The final downscaling model was used for the cellwise estimation of monthly precipitation sums, the number of rainy days and the maximum daily precipitation amount with a spatial resolution of 1 km2. The model was found to sufficiently capture the temporal and spatial variations in precipitation rates in the highly structured target area and allows for a detailed analysis of the precipitation distribution. A concluding sensitivity analysis of the ANN model reveals the effect of the atmospheric and topographic predictor variables on the precipitation estimations in the climatically diverse subregions.

scholarly journals Anticorrelated observed and modeled trends in dissolved oceanic oxygen over the last 50 years

2012 ◽  
Vol 9 (4) ◽  
pp. 4595-4626 ◽  
Author(s):  
L. Stramma ◽  
A. Oschlies ◽  
S. Schmidtko
Keyword(s):  
Large Scale ◽  
Model Comparison ◽  
Numerical Models ◽  
Regional Patterns ◽  
The Past ◽  
Tropical Oceans ◽  
Model Configuration ◽  
Pattern Correlation ◽  
Increasing Trends ◽  
Global Mean

Abstract. Observations and model runs indicate trends in dissolved oxygen (DO) associated with current and ongoing global warming. However, a large-scale observation-to-model comparison has been missing and is presented here. This study presents a first global compilation of DO measurements covering the last 50 years. It shows declining upper-ocean DO levels in many regions, especially the tropical oceans, whereas areas with increasing trends are found in the subtropics and in some subpolar regions. For the Atlantic Ocean south of 20° N, the DO history could even be extended back to about 70 years, showing decreasing DO in the subtropical South Atlantic. The global mean DO trend between 50° S and 50° N at 300 dbar for the period 1960 to 2010 is −0.063 μmol kg−1 yr−1. Results of a numerical biogeochemical Earth system model reveal that the magnitude of the observed change is consistent with CO2-induced climate change. However, the correlation between simulated and observed patterns of past DO change is negative, indicating that the model does not correctly reproduce the processes responsible for observed regional oxygen changes in the past 50 years. A negative pattern correlation is also obtained for model configurations with particularly low and particularly high diapycnal mixing, for a configuration that assumes a CO2-induced enhancement of the C:N ratios of exported organic matter and irrespective of whether climatological or realistic winds from reanalysis products are used to force the model. Depending on the model configuration the 300 dbar DO trend between 50° S and 50° N is −0.026 to −0.046 μmol kg−1 yr−1. Although numerical models reproduce the overall sign and, to some extent, magnitude of observed ocean deoxygenation, this degree of realism does not necessarily apply to simulated regional patterns and the representation of processes involved in their generation. Further analysis of the processes that can explain the discrepancies between observed and modeled DO trends is required to better understand the climate sensitivity of oceanic oxygen fields and predict potential DO changes in the future.

Response of Tropical Cyclone Potential Intensity to a Global Warming Scenario in the IPCC AR4 CGCMs

2010 ◽  
Vol 23 (6) ◽  
pp. 1354-1373 ◽  
Author(s):  
Jinhua Yu ◽  
Yuqing Wang ◽  
Kevin Hamilton
Keyword(s):  
Global Warming ◽  
Tropical Cyclone ◽  
Large Scale ◽  
Linear Trend ◽  
Relative Effect ◽  
Vertical Shear ◽  
Model Parameters ◽  
Climate Projections ◽  
South Indian ◽  
Projected Changes

Abstract This paper reports on an analysis of the tropical cyclone (TC) potential intensity (PI) and its control parameters in transient global warming simulations. Specifically, the TC PI is calculated for phase 3 of the Coupled Model Intercomparison Project (CMIP3) integrations during the first 70 yr of a transient run forced by a 1% yr−1 CO2 increase. The linear trend over the period is used to project a 70-yr change in relevant model parameters. The results for a 15-model ensemble-mean climate projection show that the thermodynamic potential intensity (THPI) increases on average by 1.0% to ∼3.1% over various TC basins, which is mainly attributed to changes in the disequilibrium in enthalpy between the ocean and atmosphere in the transient response to increasing CO2 concentrations. This modest projected increase in THPI is consistent with that found in other recent studies. In this paper the effects of evolving large-scale dynamical factors on the projected TC PI are also quantified, using an empirical formation that takes into account the effects of vertical shear and translational speed based on a statistical analysis of present-day observations. Including the dynamical efficiency in the formulation of PI leads to larger projected changes in PI relative to that obtained using just THPI in some basins and smaller projected changes in others. The inclusion of the dynamical efficiency has the largest relative effect in the main development region (MDR) of the North Atlantic, where it leads to a 50% reduction in the projected PI change. Results are also presented for the basin-averaged changes in PI for the climate projections from each of the 15 individual models. There is considerable variation among the results for individual model projections, and for some models the projected increase in PI in the eastern Pacific and south Indian Ocean regions exceeds 10%.

Preliminary analysis and main problems of instrumental measurement complex at the Vernadsky Antarctic Station

2021 ◽  
Author(s):  
Denys Pishniak ◽  
Svitlana Krakovska ◽  
Anastasia Chyhareva ◽  
Sergii Razumnyi
Keyword(s):  
Measurement Data ◽  
Bias Reduction ◽  
Small Scale ◽  
High Temporal Resolution ◽  
Monthly Precipitation ◽  
Polar Regions ◽  
Indirect Methods ◽  
Precipitation Measurement ◽  
Precipitation Gauge ◽  
The Antarctic

&lt;p&gt;Measurements of precipitation has always had well known difficulties that caused inaccuracies. This is especially acute in Polar regions where prevailing solid precipitation is accomplished with strong winds. Alternatively some indirect methods of precipitation measurements still in development and numerous meteorological instruments have been created on their basis.&lt;/p&gt;&lt;p&gt;The Akademik Vernadsky station is located in the Antarctic Peninsula region with a large amount of precipitation and &amp;#160;the problem of its measuring has always been relevant here. Although the data of monthly precipitation have been found for Vernadsky (Faraday) station since 1964, the first standard Tretyakov precipitation gauge was set up there only in 1997. But in recent years, several new instruments for indirect precipitation measurement have been installed at the meteorological site. The consistency of their data are the subject for this study.&amp;#160;&lt;/p&gt;&lt;p&gt;Direct comparison of all measurement devices as well as investigation of their estimations dependencies from other meteorological parameters are analysed and will be presented for the period 2019-2020. Originally various instruments showed huge differences in precipitation estimates. Deep analysis and correction of the measurement results according to weather conditions is obviously needed for bias reduction. But the local features of the extremely heterogeneous underlying surface of the region affect the vertical component of the wind, and can cause the natural small scale precipitation variability.&amp;#160;&lt;/p&gt;&lt;p&gt;The advantages of indirect methods for precipitation measuring is a high sensitivity to registering even individual falling precipitation particles and, hence, the really high temporal resolution of the data. Therefore, it can be used for investigation of physical atmospheric processes. As an example, the case study of a cyclone with precipitation phase transition over Vernadsky station on December 5-6, 2020 is investigated and will be presented. A comparison of the measurement data of various devices (Tretyakov Precipitation Gauge, Snow Stick, Vaisala PWD22, Lufft WS100, METEK MRR-PRO) and the ERA-5 reanalysis was carried out. A vertical radar MRR-PRO is of special interest as a measuring instrument for polar regions because it can ignore surface snow transport and has proved reliability in the Antarctic environment recently. In Marine Antarctica this device can identify the height of precipitation melting and also show a number of other useful parameters. This complex of precipitation measurement instruments is planned to be used in the frames of the forthcoming YOPP-SH field campayne.&lt;/p&gt;

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