Tanzania. General Climate. UNDP Climate Change Country Profiles. C. McSweeney 1, M. New 1,2 and G. Lizcano 1
|
|
|
- Blaise Hudson
- 5 years ago
- Views:
Transcription
1 UNDPClimateChangeCountryProfiles Tanzania C.McSweeney 1,M.New 1,2 andg.lizcano 1 1.SchoolofGeographyandEnvironment,UniversityofOxford. 2.TyndallCentreforClimateChangeResearch GeneralClimate Tanzanialiesjustsouthoftheequator,at111 Sandhasatropicalclimatewithregionalvariations duetotopography.withtheexceptionofanarrowcoastalstrip,mostoftanzaniaishighland.the greaterpartoftanzaniaisacentralplateauofaround m,punctuatedwithmountain ranges(includingkilimanjaro,5895m).thecoastalregionsoftanzaniaarewarmandhumid,with temperatures25to17 Cthroughmostoftheyear,dippingjustbelow25 Cinthecoolestmonths (JJAS).Thehighlandregionsaremoretemperate,withtemperaturesaround2023 Cthroughout theyear,droppingbyonlyadegreeorsoinjjas. SeasonalrainfallinTanzaniaisdrivenmainlybythemigrationoftheInterTropicalConvergence Zone(ITCZ),relativelynarrowbeltofverylowpressureandheavyprecipitationthatformsnearthe earth sequator.theexactpositionoftheitczchangesoverthecourseoftheyear,migrating southwardsthroughtanzaniainoctobertodecember,reachingthesouthofthecountryinjanuary andfebruary,andreturningnorthwardsinmarch,aprilandmay.thiscausesthenorthandeastof Tanzaniaexperiencestwodistinctwetperiods the short rainsinoctobertodecemberandthe long rainsinmarchtomay,whilstthesouthern,westernandcentralpartsofthecountry experienceonewetseasonthatcontinuesoctoberthroughtoaprilormay.theamountofrainfall fallingintheseseasonsisusually50200mmpermonthbutvariesgreatlybetweenregions,andcan beasmuchas300mmpermonthinthewettestregionsandseasons.themovementsoftheitcz aresensitivetovariationsinindianoceanseasurfacetemperaturesandvaryfromyeartoyear, hencetheonset,durationandintensityoftheserainfallsvaryconsiderablyinterannually.oneof themostwelldocumentedoceaninfluencesonrainfallinthisregionistheelniñosouthern Oscillation(ENSO).ElNiñoepisodesusuallycausegreaterthanaveragerainfallsintheshortrainfall season(ond),whilstcoldphases(laniña)bringadrierthanaverageseason. 1
2 RecentClimateTrends Temperature Meanannualtemperaturehasincreasedby1.0 Csince1960,anaveragerateof0.23 Cper decade.thisincreaseintemperaturehasbeenmostrapidinjfandslowestinjjas. Dailytemperatureobservationsshowonlysmallincreasingtrendsinthefrequencyhot days 1,butmuchlargerincreasingtrendsinthefrequencyofhotnights. o Theaveragenumberof hot daysintanzaniahasonlyincreasedsignificantlyindjf whentheaveragenumberofhotdjfdayshasincreasedby2.5dayspermonth(an additional8.2%ofdjfdays)between1960and2003. o Theaveragenumberof hot nightsperyearincreasedby50(anadditional13.6%of nights)between1960and2003.therateofincreaseisseenmoststronglyindjf whentheaveragenumberofhotdjfnightshasincreasedby6dayspermonth(an additional19.8%ofdjfnights)overthisperiod. Thefrequencyofcold 2 dayshasnotchangeddiscernibly,despitetheobservedincreasesin meantemperature.thefrequencyofcoldnightshas,however,decreasedsignificantlyinall seasons. o Theaveragenumberof cold nightsperyearhasdecreasedby34(9.3%ofdays). ThisrateofdecreaseismostrapidinDJFwhentheaveragenumberofcoldDJF nightshasdecreasedby3.6nightspermonth(11.5%ofdjfnights)overthisperiod. Precipitation ObservationsofrainfalloverTanzaniashowstatisticallysignificantdecreasingtrendsin annual,andjjasandmamrainfall.annualrainfallhasdecreasedatanaveragerateof 2.8mmpermonth(3.3%)perdecade.Thegreatestannualdecreaseshaveoccurredinthe southernmostpartsoftanzania.mamandjjasrainfallshavedecreasedby4.0and0.8mm permonthperdecade,respectively(3.0%and6.0%). Trendsintheextremeindicesbasedondailyrainfalldataaremixed.Thereisnostatistically significanttrendintheproportionofrainfalloccurringinheavy 3 events.1and5dayrainfall maximashowsmall,nonstatisticallysignificantdecreasingtrends.5dayeventsshowa significantincreasingtrendof+11.03mmperdecadeinmam. 1 Hot dayor hot nightisdefinedbythetemperatureexceededon10%ofdaysornightsincurrentclimateofthatregionandseason. 2 Cold daysor cold nightsaredefinedasthetemperaturebelowwhich10%ofdaysornightsarerecordedincurrentclimateofthat regionorseason. 3 A Heavy eventisdefinedasadailyrainfalltotalwhichexceedsthethresholdthatisexceededon5%ofrainydaysincurrentthe climateofthatregionandseason. 2
3 GCMProjectionsofFutureClimate Temperature Themeanannualtemperatureisprojectedtoincreaseby1.0to2.7 Cbythe2060s,and1.5 to4.5 Cbythe2090s.Therangeofprojectionsbythe2090sunderanyoneemissions scenariois C. Allprojectionsindicateincreasesinthefrequencyofdaysandnightsthatareconsidered hot incurrentclimate. o Annually,projectionsindicatethat hot dayswilloccuron1940%ofdaysbythe 2060s,and1965%ofdaysbythe2090s. o Nightsthatareconsidered hot fortheannualclimateof197099areprojectedto increasemorequicklythathotdays,occurringon3068%ofnightsbythe2060sand 3591%ofnightsbythe2090s.Nightsthatareconsideredhotforeachseasonby standardsareprojectedtoincreaseparticularlyrapidlyinDJF,occurringon 4799%ofnightsintheseasonbythe2090s. Allprojectionsindicatedecreasesinthefrequencyofdaysandnightsthatareconsidered cold incurrentclimate.theseeventsareexpectedtobecomeexceedinglyrare,withcold daysoccurringon04%ofdaysandcoldnightsoccurringonamaximumof1%ofdays,and notatallunderthetwohigheremissionsscenarios,bythe2090s. Precipitation Projectionsofmeanrainfallarebroadlyconsistentinindicatingincreasesinannualrainfall. Theensemblerangespanschangesof4to+30%bythe2090s,andensemblemedian changesof+7to+14%. Theannualincreasesinrainfallaresimilaracrossthewholecountry,buttheseasonal patternsofchangearemorecomplex.increasesinjfrainfallaffectmostofthecountrybut particularlytheverysouth,whilsttheincreasesinmamandsonrainfallaregreatestinthe northernregionsofthecountry.injjas,rainfallincreasesintheverynorthofthecountry, butdecreasesincentralandsoutherntanzania.thispatternsuggeststhatrainfallgenerally increasesinthewetseason(s)ofeachregion. Themodelsconsistentlyprojectoverallincreasesintheproportionofrainfallthatfallsin heavyevents.theincreasesrangefrom1to14%inannualrainfallbythe2090s.increases affectmostofthecountryintheseasonsjf,mamandson. Themodelsconsistentlyprojectincreasesin1and5dayrainfallmaximabythe2090sofup to24mmin1dayevents,and4to37mmin5dayevents.thelargestincreasesareseenin MAM. 3
4 OtherRegionalClimateChangeInformation Modelsimulationsshowwidedisagreementsinprojectedchangesintheamplitudeoffuture ElNiñoevents.Tanzania sseasonalrainfallcanbestronglyinfluencedbyenso,thus contributingtouncertaintyinclimateprojectionsforthisregion. ForfurtherinformationonclimateprojectionsforAfrica,seeChristensenetal.(2007)IPCC WorkingGroupIReport: ThePhysicalScienceBasis,Chapter11(RegionalClimate projections):section11.2(africa). 4
5 DataSummary Observed Mean Observed Trend Projectedchangesbythe 2030s Projectedchangesbythe 2060s Projectedchangesbythe 2090s Min Median Max Min Median Max Min Median Max Temperature (changein C ( C) perdecade) Changein C Changein C Changein C A Annual * A1B B A JF * A1B B A MAM * A1B B A JJAS * A1B B A OND * A1B B Precipitation (mmper month) (changein mmper decade) Changeinmmpermonth Changeinmmpermonth Changeinmmpermonth A Annual * A1B B A JF A1B B A MAM * A1B B A JJAS * A1B B A OND A1B B Precipitation(%) (mmper month) (changein% perdecade) %Change %Change %Change A Annual * A1B B A JF A1B B A MAM * A1B B A JJAS * A1B B A OND A1B B
6 Observed Mean Observed Trend Projectedchangesbythe 2030s Projectedchangesbythe 2060s Projectedchangesbythe 2090s Min Median Max Min Median Max Min Median Max % Frequency Changein frequency perdecade Future%frequency Future%frequency FrequencyofHotDays(TX90p) A2 **** **** **** Annual A1B **** **** **** B1 **** **** **** A2 **** **** **** JF 13.2 (1.91*) A1B **** **** **** (DJF) B1 **** **** **** A2 **** **** **** MAM A1B **** **** **** B1 **** **** **** A2 **** **** **** JJAS 11.1 (0.32) A1B **** **** **** (JJA) B1 **** **** **** A2 **** **** **** OND A1B **** **** **** B1 **** **** **** FrequencyofHotNights(TN90p) A2 **** **** **** Annual * A1B **** **** **** B1 **** **** **** A2 **** **** **** JF 13.2 (4.60*) A1B **** **** **** (DJF) B1 **** **** **** A2 **** **** **** MAM * A1B **** **** **** B1 **** **** **** A2 **** **** **** JJAS 9.4 (1.52) A1B **** **** **** (JJA) B1 **** **** **** A2 **** **** **** OND A1B **** **** **** B1 **** **** **** FrequencyofColdDays(TX10p) A2 **** **** **** Annual A1B **** **** **** B1 **** **** **** A2 **** **** **** JF 8.4 (0.47) A1B **** **** **** (DJF) B1 **** **** **** A2 **** **** **** MAM A1B **** **** **** B1 **** **** **** A2 **** **** **** JJAS 8.5 (0.15) A1B **** **** **** (JJA) B1 **** **** **** A2 **** **** **** OND A1B **** **** **** B1 **** **** **** FrequencyofColdNights(TN10p) A2 **** **** **** Annual * A1B **** **** **** B1 **** **** **** A2 **** **** **** JF 8.0 (2.68*) A1B **** **** **** (DJF) B1 **** **** **** A2 **** **** **** MAM * A1B **** **** **** B1 **** **** **** A2 **** **** **** JJAS 8.2 (2.35*) A1B **** **** **** (JJA) B1 **** **** **** A2 **** **** **** OND * A1B **** **** **** B1 **** **** ****
7 Observed Mean Observed Trend Projectedchangesbythe 2030s Projectedchangesbythe 2060s Projectedchangesbythe 2090s Min Median Max Min Median Max Min Median Max %totalrainfallfallinginheavyevents(r95pct) Changein% % perdecade Changein% Changein% A2 **** **** **** Annual A1B **** **** **** B1 **** **** **** A2 **** **** **** JF **** **** A1B **** **** **** (DJF) B1 **** **** **** A2 **** **** **** MAM **** **** A1B **** **** **** B1 **** **** **** A2 **** **** **** JJAS **** **** A1B **** **** **** (JJA) B1 **** **** **** A2 **** **** **** OND **** **** A1B **** **** **** B1 **** **** **** Maximum1dayrainfall(RX1day) Changein mm mmper Changeinmm Changeinmm decade A2 **** **** **** Annual **** **** A1B **** **** **** B1 **** **** **** A2 **** **** **** JF 29.8 (1.79) A1B **** **** **** (DJF) B1 **** **** **** A2 **** **** **** MAM **** **** A1B **** **** **** B1 **** **** **** A2 **** **** **** JJAS 8.6 (0.56) A1B **** **** **** (JJA) B1 **** **** **** A2 **** **** **** OND A1B **** **** **** B1 **** **** **** Maximum5dayRainfall(RX5day) Changein mm mmper Changeinmm Changeinmm decade A2 **** **** **** Annual A1B **** **** **** B1 **** **** **** A2 **** **** **** JF 52.2 (0.93) A1B **** **** **** (DJF) B1 **** **** **** A2 **** **** **** MAM * A1B **** **** **** B1 **** **** **** A2 **** **** **** JJAS 13.4 (1.39) A1B **** **** **** (JJA) B1 **** **** **** A2 **** **** **** OND A1B **** **** **** B1 **** **** **** *indicatestrendisstatisticallysignificantat95%confidence ****indicatesdataarenotavailable Bracketedtrendvaluesforextremesindicesindicatevaluesfortheclosestseasonsthatdataisavailable.Seedocumentation. 7
8 Figure 1: Trends in annual and seasonal mean temperature for the recent past and projected future. All values shown are anomalies, relative to the mean climate. Black curves show the mean of observed data from 1960 to 2006, Brown curves show the median (solid line) and range (shading) of model simulations of recent climate across an ensemble of 15 models. Coloured lines from 2006 onwards show the median (solid line) and range (shading) of the ensemble projections of climate under three emissions scenarios. Coloured bars on the right-hand side of the projections summarise the range of mean climates simulated by the 15 models for each emissions scenario. 8
9 Figure 2: Spatial patterns of projected change in mean annual and seasonal temperature for 10-year periods in the future under the SRES A2 scenario. All values are anomalies relative to the mean climate of In each grid box, the central value gives the ensemble median and the values in the upper and lower corners give the ensemble maximum and minimum. 9
10 Figure 3: Trends in monthly precipitation for the recent past and projected future. All values shown are anomalies,relative to the mean climate. See Figure 1 for details. 10
11 Figure 4: Spatial patterns of projected change in monthly precipitation for 10-year periods in the future under the SRES A2 scenario. All values are anomalies relative to the mean climate of See Figure 2 for details. 11
12 Figure 5: Trends in monthly precipitation for the recent past and projected future. All values shown are percentage anomalies, relative to the mean climate. See Figure 1 for details. 12
13 Figure 6: Spatial patterns of projected change in monthly precipitation for 10-year periods in the future under the SRES A2 scenario. All values are percentage anomalies relative to the mean climate of See Figure 2 for details. 13
14 Figure 7: Trends in Hot-day frequency for the recent past and projected future. See Figure 1 for details. 14
15 Figure 8: Spatial patterns of projected change in Hot-day frequency for 10-year periods in the future under the SRES A2 scenario. See Figure 2 for details. 15
16 Figure 9: Trends in hot-night frequency for the recent past and projected future. See Figure 1 for details. 16
17 Figure 10: Spatial patterns of projected change in hot-night frequency for 10-year periods in the future under the SRES A2 scenario. See Figure 2 for details. 17
18 Figure 11: Trends in cold-day frequency for the recent past and projected future. See Figure 1 for details. 18
19 Figure 12: Spatial patterns of projected change in cold-day frequency for 10-year periods in the future under the SRES A2 scenario. See Figure 2 for details. 19
20 Figure 13: Trends in cold-night frequency for the recent past and projected future. See Figure 1 for details. 20
21 Figure 14: Spatial patterns of projected change in cold-night frequency for 10-year periods in the future under the SRES A2 scenario. See Figure 2 for details. 21
22 Figure 15: Trends in the proportion of precipitation falling in heavy events for the recent past and projected future. All values shown are anomalies, relative to the mean climate. See Figure 1 for details. 22
23 Figure 16: Spatial patterns of projected change in the proportion of precipitation falling in heavy events for 10-year periods in the future under the SRES A2 scenario. All values are anomalies relative to the mean climate of See Figure 2 for details. 23
24 Figure 17: Trends in maximum 1-day rainfall for the recent past and projected future. All values shown are anomalies, relative to the mean climate. See Figure 1 for details. 24
25 Figure 18: Spatial patterns of maximum 1-day rainfall for 10-year periods in the future under the SRES A2 scenario. All values are anomalies relative to the mean climate of See Figure 2 for details. 25
26 Figure 19: Trends in maximum 5-day rainfall for the recent past and projected future. All values shown are anomalies, relative to the mean climate. See Figure 1 for details. 26
27 Figure 20: Spatial patterns of projected change in maximum 5-day rainfall for 10-year periods in the future under the SRES A2 scenario. All values are anomalies relative to the mean climate of See Figure 2 for details. 27
Table S1 Figures S1 to S10
Table S Figures S to S Table S. Comparison and inter-correlation between AeroCom I and AeroCom II individual models bias in simulating 27-29 CALIOP-derived Zα-6 km and AOD diagnostics over the 2 selected
Supporting Information
Supporting Information van der Werf et al. 10.1073/pnas.0803375105 Fig. S1. Fire locations (number of detected fires during 2000 ) superimposed on a drainage map (blue). Note how most fires occur along
Performance Evaluation of a Water Resources System under Varying Climatic Conditions: Reliability, Resilience, Vulnerability and Beyond
Performance Evaluation of a Water Resources System under Varying Climatic Conditions: Reliability, Resilience, Vulnerability and Beyond Tirusew Asefa, Ph.D., P.E., John Clayton, Ph.D., P.E., Alison Adams,
University of Bristol - Explore Bristol Research
Huntley, B., Collingham, Y. C., Singarayer, J. S., Valdes, P. J., Barnard, P., Midgley, G. F.,... Ohlemüller, R. (2016). Explaining patterns of avian diversity and endemicity: Climate and biomes of southern
4th VALUE Training School Validation of Regional Climate Change Projections. Pitfalls II
4th VALUE Training School Validation of Regional Climate Change Projections Pitfalls II Douglas Maraun Wegener Center for Climate and Global Change Douglas Maraun MOS ICTP, Trieste 1 / 53 Outline Perfect
Selecting climate change scenarios using impact-relevant sensitivities
Geophysical Research Letters Supporting Information for Selecting climate change scenarios using impact-relevant sensitivities Julie A. Vano A* John B. Kim B David E. Rupp A Philip W. Mote A A Oregon Climate
Projected 2011 Missouri River Flood Elevations
Projected 2011 Missouri River Flood Elevations Kansas City District, US Army Corps of Engineers The following table presents two water surface profiles based on the likely range of flows that are expected
Monthly, Seasonal and Annual Rainfall Time Series for All-India, Homogeneous Regions and Meteorological Subdivisions:
ISSN 0252-1075 Contribution from IITM Research Report No. RR-138 ESSO/IITM/STCVP/SR/02(2017)/189 Monthly, Seasonal and Annual Rainfall Time Series for All-India, Homogeneous Regions and Meteorological
Arctic Freshwater Flux and Change
Arctic Freshwater Flux and Change Daqing Yang, Doug Kane, Sveta Berezovskaya Water and Environment Research Center, Univ. of Alaska Fairbanks Main Topics Large Arctic River Streamflow Regime and Change
NARCCAP Model Comparison of Extreme Rainfall Intensity in the Continental US
NARCCAP Model Comparison of Extreme Rainfall Intensity in the Continental US Peng Gao and Greg Carbone Carolinas Integrated Sciences and Assessments (CISA) Department of Geography, University of South
2016 Meteorological and Oceanographic Summary for the Bocas del Toro Research Station. Prepared by: Steven Paton
0 2016 Meteorological and Oceanographic Summary for the Bocas del Toro Research Station Prepared by: Steven Paton 1 Introduction This is the forth of a series of yearly reports summarising the past year
Electric vehicles and heat pumps providing flexibility to facilitate integration of large amounts of intermittent renewables
Electric vehicles and heat pumps providing flexibility to facilitate integration of large amounts of intermittent renewables IEA DSM Agreement Task XVII workshop July 9 th, Petten, The Netherlands Frans
Local Climatological Data Summary Aurora, Illinois
SWS Miscellaneous Publication 98-15 STATE OF ILLINOIS DEPARTMENT OF NATURAL RESOURCES Local Climatological Data Summary Aurora, Illinois 1901-1996 Herbert Hoffman 1, Audrey A. Bryan 2 and Wayne Wendland
CITY OF VANCOUVER ADMINISTRATIVE REPORT
Supports Item No. 1 T&T Committee Agenda May 13, 2008 CITY OF VANCOUVER ADMINISTRATIVE REPORT Report Date: April 29, 2008 Author: Don Klimchuk Phone No.: 604.873.7345 RTS No.: 07283 VanRIMS No.: 13-1400-10
2014 Meteorological and Oceanographic Summary for the Bocas del Toro Research Station. Prepared by: Steven Paton
0 2014 Meteorological and Oceanographic Summary for the Bocas del Toro Research Station Prepared by: Steven Paton 1 Introduction This is the second of a series of yearly reports summarising the past year
Tabuchi Electric Inverter Quality & Reliability Overview February 2017
Tabuchi Electric Inverter Quality & Reliability Overview February 2017 Copyright 2017 Tabuchi Electric Company of America Limited. 1 Tabuchi Corporate History & Philosophy Established in 1925, Tabuchi
Textile Per Capita Consumption
November 2017 Textile Per Capita Consumption 2005-2022 Part 1: Lower middle income countries CHF300.- Table of Contents Preface... 4 Sources... 5 Definitions... 6 Charts... 7 Executive Summary... 9 Country
Developments in Electrification and Implications for the United States Electric Industry U.S. Department of Energy Perspective
Developments in Electrification and Implications for the United States Electric Industry U.S. Department of Energy Perspective Katie Jereza, Deputy Assistant Secretary October 18, 2017 U.S. Department
Grid Code Frequency Response Working Group Stewart Whyte System Development
Grid Code Frequency Response Working Group Stewart Whyte System Development Place your chosen image here. The four corners must just cover the arrow tips. For covers, the three pictures should be the same
Local Climatological (Data Summary Molim, Illinois
SWS Miscellaneous Publication 98-13 STATE OF ILLINOIS DEPARTMENT OF ENERGY AND NATURAL RESOURCES Local Climatological (Data Summary Molim, Illinois 1872-1992 by Audrey A. Bryan and Wayne Wendland Climatological
Offshore Platform Installations
Offshore Platform Installations GLOBAL POWER TECHNOLOGIES Power where you need it. www.genthermglobalpower.com ADVANTAGES OF THERMOELECTRIC GENERATORS FOR OFFSHORE PLATFORM INSTALLATIONS Offshore operators
Traffic Data For Mechanistic Pavement Design
NCHRP 1-391 Traffic Data For Mechanistic Pavement Design NCHRP 1-391 Required traffic loads are defined by the NCHRP 1-37A project software NCHRP 1-39 supplies a more robust mechanism to enter that data
CAM5.4 simulations: the good, the bad and the ugly. Cécile Hannay and Rich Neale (AMP)
CAM5.4 simulations: the good, the bad and the ugly Cécile Hannay and Rich Neale (AMP) The CAM family Model CAM4 CCSM4 CAM5.1 CESM1.0.3 CAM5.3 CESM1.2.0 Release Apr 2010 June 2011 June 2013 PBL HB UW UW
PyeongChang Weather Report. (April 2017) The PyeongChang Organizing Committee for the 2018 Olympic & Paralympic Winter Games
PyeongChang 218 Weather Report (April 217) The PyeongChang Organizing Committee for the 218 Olympic & Paralympic Winter Games Sport Planning Department Meteorology & Climate Team Contents 1. Characteristics
2016 Meteorological Summary for the Galeta Marine Island Laboratory. Prepared by: Steven Paton
0 2016 Meteorological Summary for the Galeta Marine Island Laboratory Prepared by: Steven Paton 1 Introduction This is the fourth in a series of yearly reports summarising the past year s Smithsonian Tropical
2017 Meteorological Summary for the Galeta Marine Island Laboratory. Prepared by: Steven Paton
0 2017 Meteorological Summary for the Galeta Marine Island Laboratory Prepared by: Steven Paton 1 Introduction This is the 5 th in a series of yearly reports summarising the past year s Smithsonian Tropical
D G A G R I D A S H B O A R D : A P P L E S
75 79 60 56 49 74 65 59 54 42 76 63 58 53 78 55 42 43 79 44 81 63 47 83 64 59 53 48 Sources: Eurostat, MSs notifications, DG Agri, Comext, Comtrade, GTA, ITC, AMI, Expert groups, Freshfel, Wapa. 89 68
Forecast El Niño Southern Oscillation Phases and Best Irrigation Strategies to Increase Cotton Yield
Forecast El Niño Southern Oscillation Phases and Best Irrigation Strategies to Increase Cotton Yield R. Louis Baumhardt 1, Steve A. Mauget 2, Prasanna H. Gowda 1, David K. Brauer 1 and Gary W. Marek 1
FOR IMMEDIATE RELEASE
Article No. 7845 Available on www.roymorgan.com Roy Morgan Unemployment Profile Friday, 18 January 2019 Unemployment in December is 9.7% and under-employment is 8.8% FOR IMMEDIATE RELEASE Australian unemployment
History gives hope for wheat rally Be sure to reward $2 rally. By Bryce Knorr, Senior Grain Market Analyst
History gives hope for wheat rally Be sure to reward $2 rally By Bryce Knorr, Senior Grain Market Analyst For years the wheat market stagnated waiting for a single trigger: A sharp reduction in global
The$Eastward$Shift$of$the$Walker$Circulation$ in$response$to$global$warming$and$its$ relationship$to$enso$variability$
1 2 3 4 5 6 7 8 9 1 11 12 13 14 15 16 17 18 19 2 21 22 23 24 25 26 27 28 29 3 31 32 The$Eastward$Shift$of$the$Walker$Circulation$ in$response$to$global$warming$and$its$ relationship$to$enso$variability$
LOCAL CLIMATOLOGICAL DATA
ILLINOIS STATE WATER SURVEY DIVISION URBANA, ILLINOIS ISWS MP-21 Archive SWS0964 Illinois State Water Survey LOCAL CLIMATOLOGICAL DATA FDR HILLSBORO, IL. 1901-1962 LOCAL CLIMATOLOGICAL DATA 1901-1962 HILLSBORO
Economic Dispatch and SCADA for Diesel Efficiency Improvements *
Economic Dispatch and SCADA for Diesel Efficiency Improvements * 2009 International Wind-Diesel Workshop Ottawa, Ontario, Canada June 2, 2009 Richard Wies, UAF Electrical and Computer Engineering A project
1 Faculty advisor: Roland Geyer
Reducing Greenhouse Gas Emissions with Hybrid-Electric Vehicles: An Environmental and Economic Analysis By: Kristina Estudillo, Jonathan Koehn, Catherine Levy, Tim Olsen, and Christopher Taylor 1 Introduction
Climatography of the United States No
Climate Division: CA 5 NWS Call Sign: Month (1) Min (2) Month(1) Extremes Lowest (2) Temperature ( F) Lowest Month(1) Degree s (1) Base Temp 65 Heating Cooling 100 Number of s (3) Jan 45.9 26.0 36.0 67
Climatography of the United States No
Climate Division: MA 3 NWS Call Sign: BOS Month (1) Min (2) Month(1) Extremes Lowest (2) Temperature ( F) Lowest Month(1) Degree s (1) Base Temp 65 Heating Cooling 100 Number of s (3) 36.5 22.1 29.3 72
6. Hydroelectric Power Modeling
6. Hydroelectric Power Modeling 6.1 MODEL DESCRIPTION The hydroelectric power model used for the FRWP EIR/EIS analysis, LongTermGen, was recently developed by the Western Area Power Administration (WAPA).
Using big data to relieve energy distribution stresses
The European Commission s science and knowledge service Joint Research Centre Using big data to relieve energy distribution stresses T. Efthimiadis R. Carvalho, L. Buzna C.-F. Covrig, M. Masera, J.M. Blanco
Climatography of the United States No
Climate Division: WY 9 NWS Call Sign: LND Temperature ( F) Month (1) Min (2) Month(1) Extremes Lowest (2) Lowest Month(1) Degree s (1) Base Temp 65 Heating Cooling 100 Number of s (3) Jan 31.9 8.7 20.3
A Review on Grid Connected 100 kw Roof Top Solar Plant
International Journal of Recent Research and Review, Vol. X, Issue 3, September 2017 ISSN 2277 8322 A Review on Grid Connected 100 kw Roof Top Solar Plant Himanshu Bhardwaj, Tanuj Manglani, Neeraj Kumawat
CLIMATOLOGICAL SUMMARY
DEPARTMENT OF REGISTRATION AND EDUCATION CTATP OF ILLINOIS ILLINOIS STATE WATER SURVEY DIVISION URBANA, ILLINOIS ISWS MP-19 Archive ISWS Illinois State Water Survey )CAL CLIMATOLOGICAL DATA MP-19 LOCAL
Smart Solar Lighting
Smart Solar Lighting 1 PhotoLight presentation Public lighting STRAIGHT CURVE Tertiary sector or private lighting WALKWAY Hybrid operation Smart Lum P.1 P.3 P.5 P.7 P.8 P.9 Today, we are all aware of the
Past, Present-day and Future Ship Emissions
Past, Present-day and Future Ship Emissions Veronika Eyring DLR-Institute of Atmospheric Physics How to make the sea green: What to do about air pollution and greenhouse gas emissions from maritime transport
Outline. Introduction to the downscaling approach GCM selection SST bias correction CCAM model features Climate Projections for Vietnam
Outline Introduction to the downscaling approach GCM selection SST bias correction CCAM model features Climate Projections for Vietnam Rationale: why do we need more detail? Understand the likely effects
Chart Discussion: Fri-02-Nov-2018 (Harvey Stern) Chart Discussion First 30+ Deg Day after winter in Melbourne
Chart Discussion First 30+ Deg Day after winter in Melbourne 1 Chart Discussion Latest Chart & SAT PIC 1 Consensus Forecast 9am Wind Direction & Speed [Days 1 to 14 for Melbourne Airport] D - 1 D - 2 D
Residential Solar Electricity in Canada
Residential Solar Electricity in Canada Why the Solar Wave has Arrived! Dave Egles, MSc HES PV Limited 320 Mary St., Victoria BC www.hespv.com, degles@hespv.com Introduction Solar Electricity, or photovoltaics
Quarterly Market Detail - Q Townhouses and Condos Miami-Fort Lauderdale-West Palm Beach MSA
ly Market Detail - Q3 218 Summary Statistics Q3 218 Q3 217 Paid in Cash 11,55 9,91 11.7% 5,712 5,554 2.8% $19, $18, 5.6% Average Sale Price Dollar Volume $281,57 $264,562 6.2% $3.1 Billion $2.6 Billion
Determination of Monthly Means of Daily Solar Radiation and its Variability: A Summary (continued)
Introduction Section 5.3 MONTHLY MEANS OF DAILY SOLAR RADIATION AND ITS VARIABILITY R.E. Schulze, M. Maharaj and R.D. Chapman The maps and statistics of solar radiation in this Section supersede the ones
Research Interests. Power Generation Planning Toward Future Smart Electricity Systems. Social Revolution, Technology Selection and Energy Consumption
Research Interests Power Generation Planning Toward Future Smart Electricity Systems Electricity demand estimation based on bottom-up technology optimization selection Multi-objective optimization of power
NEW-VEHICLE MARKET SHARES OF CARS VERSUS LIGHT TRUCKS IN THE U.S.: RECENT TRENDS AND FUTURE OUTLOOK
SWT-2017-10 JUNE 2017 NEW-VEHICLE MARKET SHARES OF CARS VERSUS LIGHT TRUCKS IN THE U.S.: RECENT TRENDS AND FUTURE OUTLOOK MICHAEL SIVAK BRANDON SCHOETTLE SUSTAINABLE WORLDWIDE TRANSPORTATION NEW-VEHICLE
TABLE OF CONTENTS 6 MEDIUM-TERM COAL MARKET REPORT 2012
TABLE OF CONTENTS FOREWORD... 3 ACKNOWLEDGEMENTS... 5 EXECUTIVE SUMMARY... 12 Business as usual... 12 The winds of change... 12 US shale gas switches on coal in Europe... 13 From Beijing to New Delhi?...
2007 AAEA Livestock Outlook Symposium
27 AAEA Livestock Outlook Symposium Ron Plain Professor of Agricultural Economics University of Missouri-Columbia www.ssu.missouri.edu/faculty/rplain Hog Price Outlook Production Efficiency 1 Head 9.5
Meter Insights for Downtown Store
Meter Insights for Downtown Store Commodity: Analysis Period: Prepared for: Report Date: Electricity 1 December 2013-31 December 2014 Arlington Mills 12 February 2015 Electricity use over the analysis
Atmosphere and Local Environment. Trends in NO X /NO 2 emissions and ambient measurements in the UK
Trends in NO X /NO 2 emissions and ambient measurements in the UK Emily Connolly, IAQM 12 th July 2011 Presentation Overview Research Project Background Analysis of ambient measurement data Analysis of
Part 1 What Do I Want/Need in a Vehicle?
Part 1 What Do I Want/Need in a Vehicle? 1.16.2.A2 28 Total Points Possible Directions: Complete the following questions. 1. Scenario name drawn: 2. Marriage and children status: 3. Annual income: Down
SIMWIND: A Geospatial Infrastructure Model for Optimizing Wind Power Generation and Transmission
Engineering Conferences International ECI Digital Archives Modeling, Simulation, And Optimization for the 21st Century Electric Power Grid Proceedings Fall 10-23-2012 SIMWIND: A Geospatial Infrastructure
What s On The Menu. About Us. Solar Questions. The Benefits. Ontario s Solar Program Environmental Impact
What s On The Menu About Us Solar Questions The Benefits Ontario s Solar Program Cost Analysis Connect with us! 613-686-3129 reachus@maketheswitch.ca Environmental Impact Watt For Watt www.maketheswitch.ca
SOUTH AUSTRALIAN HISTORICAL MARKET INFORMATION REPORT SOUTH AUSTRALIAN ADVISORY FUNCTIONS
SOUTH AUSTRALIAN HISTORICAL MARKET INFORMATION REPORT SOUTH AUSTRALIAN ADVISORY FUNCTIONS Published: July 2015 IMPORTANT NOTICE Purpose This report is prepared by the Australian Energy Market Operator
Aging of the light vehicle fleet May 2011
Aging of the light vehicle fleet May 211 1 The Scope At an average age of 12.7 years in 21, New Zealand has one of the oldest light vehicle fleets in the developed world. This report looks at some of the
3. Atmospheric Supply of Nitrogen to the Baltic Sea in 2009
3. Atmospheric Supply of Nitrogen to the Baltic Sea in 2009 Nitrogen emission data, as well as the model results presented here have been approved by the 35 th Session of the Steering Body of EMEP in Geneva
ENERGY CONSERVATION USING VARIABLE-FREQUENCY DRIVES FOR CENTER PIVOT IRRIGATION
Proceedings of the 29th Annual Central Plains Irrigation Conference, Burlington, Colorado, Feb. 21-22, 2017 Available from CPIA, 760 N. Thompson, Colby, Kansas ENERGY CONSERVATION USING VARIABLE-FREQUENCY
Curtin Corner. Alan Langford. Chief Economist. Bankwest. 1st of September 2017
Curtin Corner 1st of September 2017 Alan Langford Chief Economist Bankwest 10 Real Gross State Product Growth 9 8 7 6 solid bars; WA actual sourced from ABS shaded bars; DAE WA forecasts solid line: actual
CCoWS. Central Coast Watershed Studies. Summary of Precipitation and Streamflow for Potrero and San Clemente Creeks in Water-Year 2007
Central Coast Watershed Studies CCoWS Summary of Precipitation and Streamflow for Potrero and San Clemente Creeks in Water-Year 2007 Santa Lucia Preserve Monterey County, California Publication No. WI-2008-01
Aglantha digitale in the Eastern North Pacific. Moira Galbraith - Institute of Ocean Sciences Mary Arai Pacific Biological Station Emeritus
Aglantha digitale in the Eastern North Pacific Moira Galbraith - Institute of Ocean Sciences Mary Arai Pacific Biological Station Emeritus Aglantha digitale: one of the most common hydromedusae in north
Appendix B CTA Transit Data Supporting Documentation
RED ED-PURPLE BYPASS PROJECT ENVIRONMENTAL ASSESSMENT AND SECTION 4(F) EVALUATION Appendix B CTA Transit Data Supporting Documentation 4( Memorandum Date: May 14, 2015 Subject: Chicago Transit Authority
WIM #41 CSAH 14, MP 14.9 CROOKSTON, MINNESOTA MAY 2013 MONTHLY REPORT
WIM #41 CSAH 14, MP 14.9 CROOKSTON, MINNESOTA MAY 2013 MONTHLY REPORT In order to understand the vehicle classes and groupings the Mn/DOT Vehicle Classification Scheme and the Vehicle Classification Groupings
Supporting Information
1 Supporting Information 2 3 4 5 6 7 8 9 10 11 12 Daily estimation of ground-level PM 2.5 concentrations over Beijing using 3 km resolution MODIS AOD Yuanyu Xie 1, Yuxuan Wang* 1,2,3, Kai Zhang 4, Wenhao
Bromacil, Diuron, and Flumioxazin Combinations for Total Vegetation Control
Bromacil, Diuron, and Flumioxazin Combinations for Total Vegetation Control Introduction Industrial vegetation managers constantly battle herbaceous vegetation in areas designated to be vegetation free
MONTHLY NEW RESIDENTIAL CONSTRUCTION, NOVEMBER 2017
FOR RELEASE AT 8:30 AM EST, TUESDAY, DECEMBER 19, MONTHLY NEW RESIDENTIAL CONSTRUCTION, NOVEMBER Release Number: CB17-206 December 19, - The U.S. Census Bureau and the U.S. Department of Housing and Urban
Master Class on PVsyst Solar Project Designing Tool 7 th June 2013
10-06-2013 Master Class on PVsyst Solar Project Designing Tool 7 th June 2013 Objectives Fundamental aspects of PV system design Performance assessment of PV systems PVSyst simulation process PV array
Copyright 2017 Integrated Environmental Solutions Limited. All rights reserved.
Tariff Analysis IES Virtual Environment Copyright 2017 Integrated Environmental Solutions Limited. All rights reserved. No part of the manual is to be copied or reproduced in any form without the express
The impact of electric vehicle development on peak demand and the load curve under different scenarios of EV integration and recharging options
The impact of electric vehicle development on peak demand and the load curve under different scenarios of EV integration and recharging options Electricity demand in France: a paradigm shift Electricity
Improved PV Module Performance Under Partial Shading Conditions
Available online at www.sciencedirect.com Energy Procedia 33 (2013 ) 248 255 PV Asia Pacific Conference 2012 Improved PV Module Performance Under Partial Shading Conditions Fei Lu a,*, Siyu Guo a, Timothy
Growth cycles in Industrial production (IIP) (percentage deviation from trend*, seasonally adjusted) Jan-00 Aug-06 Sep-94. Dec-01.
Chile The reference series The reference series used for constructing OECD Composite ing Indicator (CLI) for Chile is the index of production in total manufacturing, which is a proxy for the monthly index
Robertson County. 3 utilities: Blue Grass Energy Cooperative Fleming-Mason Energy Cooperative Kentucky Utilities DID YOU KNOW?
3 utilities: Blue Grass Energy Cooperative Fleming-Mason Energy Cooperative Kentucky Utilities Electric Service Areas DID YOU KNOW? By state-law, utilities are guaranteed a monopoly in their service territory.
NPCC Natural Gas Disruption Risk Assessment Background. Summer 2017
Background Reliance on natural gas to produce electricity in Northeast Power Coordinating Council (NPCC) Region has been increasing since 2000. The disruption of natural gas pipeline transportation capability
DRP DER Growth Scenarios Workshop. DER Forecasts for Distribution Planning- Electric Vehicles. May 3, 2017
DRP DER Growth Scenarios Workshop DER Forecasts for Distribution Planning- Electric Vehicles May 3, 2017 Presentation Outline Each IOU: 1. System Level (Service Area) Forecast 2. Disaggregation Approach
This station was updated in CRA (2015). The updated IDF curve from CRA (2015) is reproduced below, with the addition of the 20-year return period.
9. Port Aux Basques This station was updated in CRA (2015). The updated IDF curve from CRA (2015) is reproduced below, with the addition of the 20-year return period. This IDF curve was updated using 6-hr
Emission and Air Quality Trends Review
Emission and Air Quality Trends Review Georgia March 2012 1 Summary 2 Project Objective To develop and present publicly available information on trends in emissions and ambient air quality over the past
Cambridge Econometrics, 2015, Fuelling Britain s Future: A report for the European Climate Foundation, p.11.
The UK government recently committed to ban the sale of new conventional cars and vans by 2040. While this is a step in the right direction, some environmental groups have argued that it is not ambitious
2017 Meteorological and Oceanographic Summary for the Bocas del Toro Research Station. Prepared by: Steven Paton
0 2017 Meteorological and Oceanographic Summary for the Bocas del Toro Research Station Prepared by: Steven Paton 1 Introduction This is the 5 th of a series of yearly reports summarising the past year
Solar Emergency Preparedness Signs
Solar Powered Signage Powered by Powerline Technology Solar Emergency Preparedness Signs Electrical Grid Failure Caused By: Blackouts Hurricanes Ice Storms Coastal Flooding Homeland Security-Related Incidents
MONTHLY NEW RESIDENTIAL CONSTRUCTION, FEBRUARY 2017
FOR RELEASE AT 8:30 AM EDT, THURSDAY, MARCH 16, MONTHLY NEW RESIDENTIAL CONSTRUCTION, FEBRUARY Release Number: CB17-38 March 16, - The U.S. Census Bureau and the U.S. Department of Housing and Urban Development
Electric Vehicle Cost-Benefit Analyses
Electric Vehicle Cost-Benefit Analyses Results of plug-in electric vehicle modeling in eight US states Quick Take M.J. Bradley & Associates (MJB&A) evaluated the costs and States Evaluated benefits of
MONTHLY NEW RESIDENTIAL CONSTRUCTION, JULY 2017
FOR RELEASE AT 8:30 AM EDT, WEDNESDAY, AUGUST 16, MONTHLY NEW RESIDENTIAL CONSTRUCTION, JULY Release Number: CB17-133 August 16, - The U.S. Census Bureau and the U.S. Department of Housing and Urban Development
Longe-range meteorological prediction using teleconnectionsof sea surface temperature and ocean indices to regional and local climate in Thailand
Longe-range meteorological prediction using teleconnectionsof sea surface temperature and ocean indices to regional and local climate in Thailand Department of Geohydraulics and Engineering Hydrology University
Being a Member of an Energy Community:
Being a Member of an Energy Community: Assessing the Financial Benefits for End-users and Management Authority Konstantina Panagiotou Power Electronics, Machines and Control (PEMC) Research Group The University
Heavy Commercial Volumes at Selected Piezo and Wim Sites( )
Heavy Commercial Volumes at Selected Piezo and Wim Sites(2004-2011) Minnesota Department of Transportation Traffic Forecast and Analysis Section April 2012 \ Piezo and WIM Analysis Piezos record vehicle
Local Climatic Effects of Coal Fires:
Local Climatic Effects of Coal Fires: Modeling the Impacts of Subsurface Heating on Temperature and Precipitation Collapsing coal seam in NW China Anumpa Prakash- www.ehpnet1.niehs.nih.gov Global Climate
Expectations. Variables that affect system size and production. Solar Made Simple.
We Expectations Variables that affect system size and production. Solar Made Simple. var i a ble /'ve(ə)rēəbəl/ adjective 1. not consistent or having a fixed pattern; liable to change. the quality of hospital
2012 IECEE CTL PTP Workshop. Ingrid Flemming IFM Quality Services Pty Ltd
2012 IECEE CTL PTP Workshop Ingrid Flemming IFM Quality Services Pty Ltd Today QM discussion Re-cap on corrective actions (group exercise) Record keeping Creepageand Clearance discussion and exercises
MONTHLY NEW RESIDENTIAL CONSTRUCTION, APRIL 2017
FOR RELEASE AT 8:30 AM EDT, TUESDAY, MAY 16, MONTHLY NEW RESIDENTIAL CONSTRUCTION, APRIL Release Number: CB17-75 May 16, - The U.S. Census Bureau and the U.S. Department of Housing and Urban Development
Solar Energy Society of Alberta September 6, Charging Up! Edmonton s Electric Vehicle Strategy
Solar Energy Society of Alberta September 6, 2018 Charging Up! Edmonton s Electric Vehicle Strategy Strategic Alignment Implementation of Edmonton s Electric Vehicle Strategy contributes to the City s
Current Status of MICS-Asia III
Current Status of MICS-Asia III Joshua S. Fu 1,2, Kan Huang 1, Zifa Wang 3, Jun-ichi Kurokawa 4 1 Department of Civil & Environmental Engineering The University of Tennessee, USA 2 Computer Science and
Johnson County. 2 utilities: Big Sandy RECC Kentucky Power DID YOU KNOW? Residential Rate Comparison. Electric Service Areas
2 utilities: Big Sandy RECC Kentucky Power Electric Service Areas DID YOU KNOW? Map of Kentucky Electric Service Areas By state-law, utilities are guaranteed a monopoly in their service territory. Most,
2017 Adjusted Count Report February 12, 2018
A statewide multi-use trail user study and volunteer data collection program 2017 Adjusted Count Report February 12, 2018 The following report includes the final adjusted infrared (IR) counter data at
THE INFLUENCE OF TRENDS IN HEAVY VEHICLE TRAVEL ON ROAD TRAUMA IN THE LIGHT VEHICLE FLEET
THE INFLUENCE OF TRENDS IN HEAVY VEHICLE TRAVEL ON ROAD TRAUMA IN THE LIGHT VEHICLE FLEET by Amanda Delaney Stuart Newstead & Linda Watson January, 2007 Report No. 259 Project Sponsored By ii MONASH UNIVERSITY
Pedro Nunes. July 2016
Integration of PV and electric vehicles in future energy systems Pedro Nunes July 2016 1. background 2 context Sectors of energy and transport are the biggest GHG emitters in the EU (30% and 20%, respectively)
Solar Power Owner s Manual
Solar Power Owner s Manual Domestic Photovoltaic Systems Introduction Congratulations on the purchase of your solar electricity system. Not only are you protecting yourself from current and future price
WIM #41 CSAH 14, MP 14.9 CROOKSTON, MINNESOTA APRIL 2014 MONTHLY REPORT
WIM #41 CSAH 14, MP 14.9 CROOKSTON, MINNESOTA APRIL 2014 MONTHLY REPORT In order to understand the vehicle classes and groupings, the MnDOT Vehicle Classification Scheme and the Vehicle Classification