Il est généralement admis en météorologie que certains facteurs, tels que l’état global des océans et la concentration exacte de gaz à effet de serre sont de faible importance pour une prévision météo normale. De plus, si les températures de surface des océans (TSO) sont importantes, les températures des eaux profondes semblent avoir peu d’influence sur les prévisions pour les prochains jours. La raison en est que les océans réagissent lentement aux changements atmosphériques (leur inertie et capacité thermique est beaucoup plus élevée). Dès lors, l’information la plus importante pour de telles prévisions météo est l’ensemble des conditions initiales de l’atmosphère, c’est-à-dire une description des caractéristiques de l’atmosphère et des TSO au moment où le modèle commence à calculer l’évolution du temps.
(suite…)
Si nous voulons faire des prévisions sur de plus longues périodes, par exemple les prochains mois, alors les influences des conditions aux limites deviennent plus importante que celles des conditions initiales (à cause du chaos interne et du manque de prédictabilité de l’état initial). Les océans, qui fournissent certaines des conditions aux limites pour l’atmosphère, ont également assez de temps pour évoluer sensiblement, et le changement d’état océanique doit être pris en compte. De telles prévisions à long terme sont souvent appelées des prévisions saisonnières. Les prévisions saisonnières sont souvent réalisées avec des modèles couplés atmosphère-océans (plus proche des modèles climatiques), par opposition aux modèles utilisés pour les prévisions météo ordinaires qui n’incluent que l’atmosphère. Jusqu’à présent, il était supposé que des facteurs tels que les concentrations de gaz à effet de serre jouent un rôle mineur dans la technique des prévisions saisonnières. Toutefois, une nouvelle étude par Doblas-Reyes et ses co-auteurs, du Centre européen de prévisions météorologiques à moyen terme – le « centre météorologique européen » (European Centre for Medium-Range Weather Forecasts (ECMWF) – suggère qu’en mettant à jour les caractéristiques de l’effet de serre avec les moyennes annuelles observées, la technique de prévision s’améliore sensiblement.
Les implications de ces découvertes sont assez subtiles, mais importantes: nous sommes déjà en train de sentir les effets climatiques de l’augmentation des concentrations de gaz à effet de serre. Ces découvertes débouchent également sur des applications plus concrètes de nos connaissances sur les changements climatiques: en prenant en compte ces tendances (c’est-à-dire de l’information supplémentaire), nous améliorons notre capacité à faire des prévisions des saisons à l’avance. C’est aussi quelque chose qui a été observé, par exemple en Norvège, où les tendances climatiques ont comme conséquence plus de saisons chaudes que froides.
Référence:
Doblas-Reyes, F.J., R. Hagedorn, T.N. Palmer and J.-J. Morcrette:
Impact of increasing greenhouse gas concentrations in seasonal ensemble forecasts.
ECMWF Tech. Mem. #476, October 2005
(traduit par Alain Henry)
Reminds me of the UK met Office annual predictions, which forecast annual global temperatures based on atlantic multidecadal oscillation, ENSO, solar, recent volcanic activity and, crucially, radiative forcing due to GHG.
Yes, that is a good way to make a long term forecast, and it appears lacking in some current day models.
I would force feed NASA GISS GT (or other reliable) prediction as a constant and see if the weather forecast comes up with something better. May be this is done in some cases, I don’t know. What I know is that current seasonal forecasts seem to be oblivious to GT status and projections. Case in point, this year’s all time high GT seems forgotten in latest seasonal forecasts calling for a colder winter than last year.
Very interesting. So really there is no such thing as climate in the sense of average or mean conditions, but more like a trend in climate. So one must decide how often to take averages. Too long, and the climate trend is missed. Too short, and the data is too noisy.
Good luck!
[Response:Basically, the term ‘climatology’ is used to mean the ‘mean climate’ and provide a kind of reference level. But when the climate changes – one definition of a climate change is a change in the probability distribution (pdf) of a climate variable – then it’s clear that a given base line may not always be appropriate. One could use a sliding time window (i.e. always use the last say 30 years), but as you say, one may run into problems as the trend may not be captured or the interval is too short to give a sufficient statistical representation. Take Oslo for instance: the temperature between 1961 and 1990 is not very representative for the last decade (which is warmer). Usually, a pdf assumes an iid (independent and identically distributed) variable, but a non-zero trend implies a non-iid process: the data is neither independent (chronological order matters) not identically distributed. The positive side is that once the trend is known, we have more information about the process than if there were not trend. Hence, the predictive skill is boosted by the trend. -rasmus]
… “by taking these trends (i.e. extra information) into account, we improve our ability to make predictions seasons ahead”.
Trends in the Midwest in winter have been for warmer temperatures, higher dewpoints and increases in rainfall. Should that extra information be put into probabilistic river forecast products? How?
See:
http://www.crh.noaa.gov/ncrfc/ahps/esp_maps/map/m10000.php
More questions
The answer to the first question in #4 seems obvious, yes it should be put in.
What if the answer to the second question (how ?) is complex.
If how? is too complex than maybe it should not be put in now, but when?
Weather forecasters may be caught between a rock and a hard place.
Overnight minimum temperatures rarely get as low as the weather forecasters predict. Oddly enough, that’s been going on for years. Why? … If weather forecasters deviate from model guidance they need to give an explanation. But weather forecasters have been warned not to talk about climate change or global warming. That explains why they’re overnight forecasts have been biased on the low side, for years.
How come so few people are commenting on this topic (Greenhouse Gases Help Seasonal Predictions). Maybe if the topic somehow involved hurricanes then some people would comment. But!! the topic “Greenhouse Gases Help Seasonal Predictions” does involve hurricanes!!
Hurricane outlooks that are made before hurricane seasons begin ARE seasonal predictions.
Ken Robinson (#28 of next topic) was correct in his remarks that US government scientists involved in predicting hurricanes are claiming natural cycles are solely responsible for the strong hurricanes in 2005.
Their claim is not surprising … US government scientist’s involved in predicting weather and hurricanes do not support the evidence that global warming is happening due mainly to greenhouse gases accumulating in the atmosphere from anthropogenic sources.
So, if Ken heard that US government’s scientists are claiming that global warming is not happening due mainly to greenhouse gases accumulating in the atmosphere from anthropogenic sources; what would Ken say about global warming happening?
Ken?
I’m not meaning to be picking on Ken, just trying to bring up a point).
Changes (increases) in rainfall intensity, temperatures, humidity and rate of snowmelt and have occurred in recent decades, due in part to increases in CO2 concentration. Despite the observed changes, there has been a lack of research and development needed to incorporate the changes into hydrologic models for hydrologic forecasting and hydrologic outlooks. See: http://www.crh.noaa.gov/ncrfc/ahps/esp_maps/map/m10000.php
Excerpts from articles (below), have identified significant changes in rainfall intensity, temperatures, humidity and rate of snowmelt:
… “In general, the results indicated an area of increasing frequency and/or intensity of heavy storms along an axis extending from Missouri north east ward through Illinois to southern Michigan and northern Ohio. The increases appear to be greater than expected from climate variability and sufficiently large to have an impact on water-control structural designs and other aspects of applied climatology”. Rainfall Frequency Atlas of the Midwest by Floyd A. Huff and James R. Angel, Illinois State Water Survey, Champaign, IL, Bulletin 71, 1992 http://www.sws.uiuc.edu/pubdoc/B/ISWSB-71.pdf
“Especially since about 1950, that the incidence of these extreme floods has been increasing way more than you’d expect from just chance alone,” Knox said. … He studied the sediments from the Mississippi River beds, which provided him evidence of flood activity as far back as 7,000 years ago. … [James Knox, professor of geography at the University of Wisconsin, Madison] http://www.channel3000.com/entertainment/4411737/detail.html
… “dust emissions have a wide impact on climate and weather, from modifying rainfall thousands of miles away, to influencing hurricane intensity and affecting air quality”. Heavy Rains Can Make More Dust In Earth’s Driest Spots http://www.terradaily.com/news/water-earth-05zi.html
… “Conclusions on the Timing of Snowmelt Runoff and Humidity
1) Trends were shown for recent earlier in the year annual snowmelt runoff at three river stations within the Northern Great Plains and Upper Midwest.
2) Trends were shown for recent increasing dewpoint averages for January, February, and March but not April.”
http://www.mnforsustain.org/climate_snowmelt_dewpoints_minnesota_neuman.htm
Re#6, If you squint hard enough, you might be able to get a glimpse of those guys with AK-47s pointed at the Weather Channel people – just in case they slip up.
Re: #9, “Re#6, If you squint hard enough, you might be able to get a glimpse of those guys with AK-47s pointed at the Weather Channel people – just in case they slip up.”
Now that is out of line. It’s not about AK-47s, but advertising revenues.
Re #7. I was at a conference for a week, so I missed this post. But I agree, this is an important topic.
I often wonder, when weathermen say, “…above (or below) the average…” if they are averaging the weather stats up to the present day, which would include the impact of GW. So, I guess the average keeps getting a bit higher. But the viewer probably assumes the average has been a constant over the last 100 or so years, so they have no good comparison point to get a sense GW is happening. And since no one is telling them about GW in the media, they really only have daily weather reports to understand what might be going on. So in a way, if adding in GHGs helps in weather prediction, one negative outcome would be that weathermen will be able to say, “…as predicted…,” giving viewers a false sense that everything is normal & under control & GW is not happening, since I doubt they will mention that GHGs were used to help them make such good predictions.
We might be better off with weathermen saying, “…well, this is totally unpredicted….this is really weird weather…” Or, better yet, have the media start telling the truth about GW.
BTW, I know a weatherman whose brother is (was) in oil, which I found out much later. He did mention GW, unlike the other weatherman on the other channel in the area (who said nada about GW) — he constantly said it was NOT happening (at least up through 2002, when I left the area). My friend & I thought he seemed like a very nice man & we wondered why he was telling us garbage about GW, since it is vital that we laypeople know about this serious problem, so we can solve it. Then we found out about his brother….